SingleStore (formerly MemSQL)

SingleStore (formerly MemSQL)

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Score 9.0 out of 100
Top Rated
SingleStore (formerly MemSQL)


Recent Reviews

SingleStore and its Advantages

March 26, 2022
Real-time Analytics and Reporting can be best used in cases as Single Store is very much efficient on faster and complex query processing. …
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SingleStore and multiple advantages

March 16, 2022
the product currently is excellent, it deserves 10/10, just the fact of processing more than 1 million records in a few seconds, whatever …
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Easy to configure data sources

March 02, 2022
SingleStore is super easy to implement and use. You can deploy a cluster in a matter of clicks. The UI is very intuitive, and everything …
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TrustRadius Award Top Rated 2022
TrustRadius Award Top Rated 2021

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Product Details

What is SingleStore (formerly MemSQL)?

SingleStore (formerly MemSQL) is a Cloud DB for the Data-Intensive Era.™ The data platform market is vast and growing. SingleStore is a late-stage (Series F) scaleup, with a solution that runs on the Big 3 cloud providers and a customer base spanning every vertical, including many Fortune/Global 500 brands. SingleStore is headquartered in San Francisco with offices around the globe.

SingleStore states they are dedicated to helping businesses adapt more quickly, embrace diverse data, and accelerate digital innovation by operationalizing all data through a single database for all of their moments that matter.

SingleStore (formerly MemSQL) Screenshots

SingleStore DB Studio is a visual user interface that allows you to easily monitor, debug and interact with all of your SingleStore Clusters.SingleStore DB Studio Health Monitoring: Visually monitor the health of your clustersSingleStore DB Studio Schema Explorer: Visually understand your schemasSingleStore DB Studio Query Editor: Edit queries in MemSQL StudioSingleStore DB Studio Resource Usage: Visually monitor the usage of your resources.SingleStore DB Studio Visual Explain: Visually understand your query plan

SingleStore (formerly MemSQL) Videos

MemSQL is now SingleStore, The Database of Now™ for applications and analytics. SingleStore's distributed architecture is built for maximum ingest, fast query, and high concurrency. SingleStore runs on any public cloud or on-premises.
MemSQL Helios is now SingleStore Managed Service. In this utility IoT Demo, Domenic Ravita, Field CTO of SingleStore, walks us through using SingleStore Managed Service, the cloud-scale database cluster to ingest IoT utility meter data at 1M rows/sec, and highlights the speed ...
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MemSQL is now SingleStore. Trillion Rows Demo: Quick demo showing how to scan a trillion rows per second on SingleStore.

SingleStore (formerly MemSQL) Downloadables

SingleStore (formerly MemSQL) Integrations

SingleStore (formerly MemSQL) Competitors

SingleStore (formerly MemSQL) Technical Details

Deployment TypesOn-premise, SaaS
Operating SystemsLinux
Mobile ApplicationNo
Supported CountriesGlobal
Supported LanguagesEnglish


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Frequently Asked Questions

What is SingleStore (formerly MemSQL)?

MemSQL is a NoSQL database offering from the company of the same name in San Francisco.

What is SingleStore (formerly MemSQL)'s best feature?

Reviewers rate Performance highest, with a score of 9.4.

Who uses SingleStore (formerly MemSQL)?

The most common users of SingleStore (formerly MemSQL) are from Enterprises (1,001+ employees) and the Information Technology & Services industry.

Reviews and Ratings




(1-25 of 33)
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Samiran Mudgalkar | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
The most important use case is to load huge files into a distributed database system within a short span of time without having memory and time complexities. Whenever there is a need of transferring data for ETL during the staging phase and data warehousing stage, the load should be transferred without a lot of resource usage. Especially in the cloud space, the lesser we use the resources, the more cost-effective it is.
  • UI design
  • Perfect SQL editor and faster query execution
  • Ease of pipeline creation for data loads
  • Need to have a place to create an admin user for the first information schema database. Because when we log in, we do not have admin access by default to the system.
  • The state of the pipeline is not available if the currently available load is finished, there is extra work to check if all your files in the current load are complete.
  • The Dashboard can be a bit more simplified than having a lot of details.
1. The one place where it is required the most is, during ETL processing where the resource utilisation is optimized and faster data load is achieved.

2. The places where it is not suited are, when the data load is very low and there is not much difference achieved while execution of data loads.
Ruslan Smirnov | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
SingleStore is perfect for running data analytics workloads due to how easy it is to get data in & out. The performance and ease of use of the product are almost unmatched, which saves us a tremendous amount of time over having to spin up custom RDS instances for data analytics.
  • I was amazed at the ability to connect to the cluster with third-party clients, including native vendor-supplied MySQL command line tools.
  • The ease of exporting data from an existing MySQL database and loading it into SingleStore is impressive.
  • Speed and ease of use. Everything is streamlined for you to hit the ground running with minimal learning curve.
  • The mysqldump file required some manual massaging before it could be ingested. This was expected, and I am surprised how little manual modification is needed, but nonetheless -- this could be improved.
  • Some GUI database tools (such as MySQL Workbench) have trouble connecting and need additional configuration.
Insofar, it seems perfect for data analytics workloads and ad-hoc queries against large datasets. What we particularly like is the ease with which data can be ingested, and the speed/performance of the product. Everything is very streamlined and in one place. I am not sure where it would be inappropriate as I haven't used it long enough, but so far I like everything.
Score 9 out of 10
Vetted Review
Verified User
Review Source
Real-time Analytics and Reporting can be best used in cases as Single Store is very much efficient on faster and complex query processing. It is extremely fast on data ingestion from many sources (AWS, Azure,GCP, Files etc).
  • Faster query result as Relational Database.
  • High Availability.
  • Load data from one or more data sources.
  • Loads external data in real-time.
  • Distributed and partition feature with master-Slave architecture.
  • Load data from a file that is located on the filesystem.
  • Power up legacy database and support massive workload.
  • MySql Client can access MemSql with same query experience.
  • SingleStore has this unique ingest capability it can do parallel ingest of data from sources like S3, Azure Blob, GCS, Kafka.
  • Can be integration with Tableau for Data Visualization.
  • There should be powerful Data Visualization.
  • There can be a better Query Builder UI.
  • No implicit ordering of results by primary key.
SingleStore is very much recommendable. It has a lot of features like faster complex query execution, ANSI standard MySQL compatibility, high Data availability, and many more. Due to Distributed database architecture, the database can be scaled. It is also much useful for Real-Time data Analytic and Reporting. It powers up the legacy database and supports a massive workload.
Amarpreet Saluja | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
I am a DevOps Engineer and I work on Kubernetes, Cloud, I had a use case where I was working on creating a product that can calculate Kubernetes and cloud costs and represent it in that use case I was supposed to ingest data which was being populated in s3 to my database on which I can run queries, this using SingleStore could have been seem-less as it makes data ingestion from cloud simpler and since it helps running lot vol queries with smaller response time could have helped me lower the latency of my service.
  • Compatibility with S3 and data formats such as Parquet, JSON, and CSV
  • Can be Deployed on a Kubernetes Cluster and can be scaled seamlessly.
  • Great UI and support documentation available to look and work around.
  • Scale out capability
  • Fast data ingestion and queries
  • Can be used to lower the latencies of various services
  • Did not find support for User Defined Functions.
  • It opens a new query result tab and that feels irritating to me personally.
  • Lot of RAM required while running Developer instances locally.
Score 10 out of 10
Vetted Review
Verified User
Review Source
the product currently is excellent, it deserves 10/10, just the fact of processing more than 1 million records in a few seconds, whatever in the import of the data or the requests, it is already a great advantage, that we the developers we never dreamed of that. I'm telling you about my experience, no vacuum, because I've had nightmares with large databases, and we have to play right and left to optimize response time It is really amazing. I've never in my life worked on such a fast database
  • super fast
  • execute complex query
  • the use of several types of database
  • availablity
  • sclability
  • open many SQL Editor in same time
  • wizard for object creation (table, view, procedure...)
  • link table from other database
It can be used on any need for data treatment:
• Development
• data analysis
• migration preparation
• for data processing•......
Santhosh Yamsani | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
I'd be using SingleStore as the POC Database so as to handle data ingestion and analysis of data with a big volume of E-Learning Data. We process the data for different tenants and provide recommendations based on the processing.
  • Handing and processing Json data types fastly ( Actually I worked on it particularly )
  • It is fast and reliable
  • Pay as you use. This is quite a good feature for the customers who have load only during peak hours and doesn't have load during non-peak hours.
  • It is easy to access and can be accessed from anywhere without VPN issues as it is a cloud-based solution.
  • It is very user friendly and all options are easily navigatable.
  • Errors are easily understandable if we go wrong anywhere while doing our operations
  • Fast retrieving and reading data with JSON Formats.
Pros: 1. It is easy to access and can be accessed from anywhere without VPN issues as it is a cloud-based solution. 2. Errors are easily understandable if we go wrong anywhere while doing our operations. 3. It is very user-friendly and all options are easily navigatable. Cons: We should have templates for pulling data from different sources so that we can directly use those templates and change the names in source names and we can easily import data from different sources
Anant Sirohi | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
I'd be using SingleStore as the primary Database so as to handle real-time ingestion and analysis of data with big volume. The existing data model is working on processing batch data which is not much efficient and fast. I'll be ingesting the data from Kafka and because of the great compatibility of SingleStore with Kafka, I'll be using it to build reports on the top of the data.
  • super fast data ingestion and queries
  • commonly used formats such as csv, json and parquet are well supported
  • MySQL engine allowing the customers also to work easily
  • minimum administration needed
  • support team is quick and helpful
  • Every time i run a new query, it opens a new query result tab
  • Lot of RAM required while running Developer instances locally
  • limited information on the running queries
It would be really fast for OLTP workloads as compared to MySQL and can be used in this use case. While working on large datasets, I've experienced that SingleStore has much faster processing capabilities and is highly recommended in such scenarios.
Score 9 out of 10
Vetted Review
Verified User
Review Source
SingleStore is super easy to implement and use. You can deploy a cluster in a matter of clicks. The UI is very intuitive, and everything is easy to configure even for a new user. The look and feel are very similar to any relational DB workbench. The source configuration is very easy. Other than the good HCI, the query engine is very fast and responsive, computes huge datasets, and delivers results in seconds. Compared to MySQL, it is fast, robust, and has a good IDE. I would definitely recommend it.
  • Responsive and intuitive UI.
  • Query engine is very fast.
  • Very easy to deploy clusters and use the database.
  • Execution plan can be shown when the query is running so that the user might get information of their running queries and where to optimize them
For making up heterogenous source connections, SingleStore is very helpful since it is very easy to configure data sources. Also, in the case of large datasets, the processing capabilities of SingleStore are much faster as compared to MySQL, both being relational databases.
Score 10 out of 10
Vetted Review
Verified User
Review Source
I would use SingleStore databases on e-commerce websites where loads of data are being generated, and where you need a fast data collection to analyze user behaviors and provide real time recommendation.
  • Fast on intense data load
  • Few clicks away to have the environment setup
  • Easiness/speed to load data from different pipelines
  • Great speed on running complex queries
  • SQL Editor opens a new result tab on every query run
  • Consumption of RAM memory through browser if you have many queries
SingleStore environment is easy to adapt, it is extremely fast on collecting data from different sources (AWS, GCP or Azure), provides monitoring of activities and easy use multiple databases. It is good for analytical and recommendation based scenarios, and provides fast results on complex queries. In SingleStore platform queries execution open new tab result for each run, which makes it difficult to navigate over the results.
Score 8 out of 10
Vetted Review
Verified User
Review Source
I am exploring SingleStore as a personal interest to learn new tech skills.
  • Simple and easy interface
  • Similar SQL as we are used to with other RDBMS, so easy to start with
  • The performance is quite awesome
  • At some point I would love to enhance, i.e. it should have an indicator for progress so we are aware if something is running or is completed.
I am not certain about the price comparison of SingleStore to other vendors, but definitely, I would recommend this to those who want to keep one DB for all OLTP and OLAP transactions. It should be a good resource for analytics reports. As it has easy cluster building using any Cloud(GCP, AWS, and Azure), it can be tried by all three cloud developers. I recommend using SingleStore.
Anmol Maitra | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
  • Very easy to configure the SingleStore database.
  • Loading data was extremely easy and super fast. I loaded millions of records and it took a few seconds.
  • SingleStore seems to be an ideal database for real-time dashboards.
  • Not too many issues. Only one aggregate function I ran in the database took more than a minute to run, otherwise, performance on queries for millions of records was great.
I have worked on government projects where data is being updated frequently and data needs to be presented on a real-time basis on the dashboard for coordination, etc. SingleStore would be the most appropriate database for this use case.
Score 10 out of 10
Vetted Review
Verified User
Review Source
We are using SingleStore as our primary analytics database within our own platform (called "Pulse"). The Pulse platform is used primarily in Siemens internally, but is also available to enterprises outside of Siemens.
We offer end to end reporting & analytics services and use SingleStore to power our dashboards and reports.
  • Performance.
  • SQL-interface.
  • Relational online analytical processing (ROLAP).
  • SQL completeness (e.g. triggers).
  • Performance tuning insides.
We have not found an analytical database faster than SingleStore. While our data volume per project is usually below 100 million rows, we expect reporting and analytics queries to be executed within 100ms so that dashboard users can interactively work with their data. So if you are looking for a truly fast analytical database, SingleStore is the right database to use (even though it is also crazy fast for OLTP workloads, but that is not our use case).
Score 9 out of 10
Vetted Review
Verified User
Review Source
We use MemSQL for a particular slice of our OLAP use cases: client-facing UI dashboards that have solid query latency and data freshness requirements (generally 4 9s under 2 seconds, although we try to get under 1, and data replication and recalculation in under a second), and on small to medium size data sets (10s of GB for fact data, GBs or 10s of GBs of dimension data). It is currently owned by a data platform team that supports client-facing use cases from a number of product teams.
  • Data replication.
  • Joins.
  • Small data set processing in memory.
  • User defined functions.
  • Providing optimization options.
MemSQL is well suited for low latency, high data freshness use cases. It can scale significantly, although its in-memory usage does mean the cost of scaling to data size is higher, so I believe for very large data sets (double-triple digit TBs) where less performance (latency/freshness) is needed it may not be worth the cost. We've currently limited its usage to cases where the performance needs are very high.
Score 8 out of 10
Vetted Review
Verified User
Review Source
SingleStore is used for 2 main use cases:
  • In-house developed A/B testing analysis tool uses this to fetch raw data in real-time when end users analyse the tests using the UI.
  • Machine learning models fetch the raw data and calculate needed features in real-time instead of preprocessing the data by the data engineers.
  • Return results of complex queries scanning TBs of data in sub-seconds.
  • Customer support team answer tickets quickly and provide guidance.
  • MySQL engine which allows to query using simple MySQL drivers from different clients.
  • Queries profiling is easy to use and helps investigating performance.
  • Loading batch data using pipelines is complex.
  • No native monitoring and alerts of resources (CPU, RAM, etc.).
  • Performance is strongly coupled with number of nodes (sometimes extra nodes hurt the performance).
  • Very expensive compared to other databases.
SingleStore is well suited for analyzing big raw data in order to provide users with timely fashioned answers, as well as helping less technical teams to be independent of engineering teams and use simple SQL in order to use this data. The problem is that when there's a need to support more than a few TBs the price is very expensive and therefore it will be harder to use for applications in production when sub-second (less than 20ms) response is required.
Elad Gindi | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
We are proud to say that SKAI is a data company and our main asset is our data. My department handles the Measurements data and other incoming data sources. SingleStore is used across the organization to do real-time calculations, supply fast loading grids and store massive amounts of data. In our department, users needed to configure pre-hand MetaData for the calculations that they are basing their decision on. Our nightly batches used to work extremely hard and waste valuable time and resources to make this data available the next day (while storing it both in raw form and aggregated) and any changes required a rerun of the batch. Today the clients can configure, change and get their aggregated data in almost real-time, while the data is being stored in SingleStore only in its raw form. It allowed us to add more calculations and more data and use fewer resources on our server-side and the added bonus is that our clients love it!
  • Real-time calculation.
  • Massive data storage.
  • Real-time updates and integration.
  • Scaling up (adding memory) takes a lot of time.
  • Real-time information about lags is limited.
If you need real-time calculation and reduce DB lags in production it's ideal.

If you're looking only for storage, I would pass.
Score 10 out of 10
Vetted Review
Verified User
Review Source
We use SingleStore's managed solution as a data warehouse for the analytical analysis of quality metrics. We ingest data from Kafka and build reports on top of the data to inform our customers about various scenarios. We use hosted business intelligence tools to analyze data and answer both specific as well as open-ended questions that our customers may have.
  • Ingesting data from kafka at very high rates.
  • Easy to understand performance characteristics.
  • Hosted solution is bulletproof and always up.
  • Programming languages for ingest logic.
  • Ability to run in our own cloud accounts to save transit costs.
To get up and running quickly with a highly scalable and trusted database that can ingest data at high rates while still providing adequate query performance. We have found great use of MemSQL in heavy write, light read, and never update situations. I would strongly recommend SingleStore in that scenario.
August 10, 2021

Great product

Score 9 out of 10
Vetted Review
Verified User
Review Source
We worked with MySQL and needed a faster solution that it will be easy to integrate with.
Right now, MemSQL is our main DB and serve all of our customers.
We are transferring data with MemSQL pipelines.
In addition we are collaborating multi DBs into clusters. It is very comfortable instead of MySQL
  • Query time
  • Very easy to MySQL customers to work with
  • Easy to transfer data from other data sources
  • IN operator at where clause
  • Multi key index at columnstore
  • Enable to run cross clusters query
1. If your code is written on top of SQL, it very easy to make to work with MemSQL.
2. If you need to improve your queries performance.
3. If your you don't need to create a lot of tables at online flow (means to create a table for another query).
Score 8 out of 10
Vetted Review
Verified User
Review Source
We use it as the core database for our entire IoT platform and for all our customers.
  • We use it as a replacement for having a separate in-memory cache and a traditional disk-based database because SingleStore does both in a single package.
  • We also use the row store for storing transactional state and the column store for storing time series data. Having both in the same product is nice.
  • We get 7x compression for the time series data, which is really good for scaling.
  • We wish the product had better support for High Availability of the aggregator. Currently the indexes generated by the two different aggregators are not in the same sequential space and so our apps have more burden to deal with HA.
  • More tools for debugging issues such as high memory usage would be good.
  • The price was the one that kept us away from purchasing for the first few years. Now we are able to afford due to a promotion that gives it at 25% of the list price. Not sure if we'll continue after the promotion offer expires in another 2 years.
It's great to have a scalable story rather than spending time doing your own clustering with a bunch of MySQL servers.
Score 9 out of 10
Vetted Review
Review Source
SingleStore as the backbone for our Data Analytics platform

With SingleStore, we are able to replace multiple other databases and started migrating from on-premise to SAAS. As SingleStore provides both scenarios, the migration to the cloud will be a smart and simple one. We now use SingleStore for our data and analytics environment. As we now can use the pipelines towards our data lakes and send data via procedures into our tables, we have achieved the next step in our data management by adding additional metadata during the ingestion. Using text search and the geospatial functions adds more functionality than we had before in our previous databases. The performance and scalability are beyond our expectations.

  • The scenario to migrate on-premise and scale up to the cloud as a SAAS.
  • Using HTAP means we can now use our database for transactions and analytics.
  • The main language is similar to MYSQL, so our organization has already the knowledge to master the system.
  • The SingleStore academy is a good program to support our organization to master the environment.
  • Performance on large sets of data for analytics.
  • Row based and column based can be used and mixed.
  • Time series, geo spatial and text search function to add to our platform.
  • Scalability, so we can continue to deliver the same performance.
  • Does not yet support foreign keys.
Migrating existing databases to one instance, accelerate and scale-out existing data warehouses/analytics platforms. Replace HIVE for SingleStore, which will boost your overall performance and support your data management. Get ready for the cloud by using it on-premise, your own cloud/data center, or as a SAAS. The functionality is the same and migrating will be smooth.
Virginie Aelst | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source

UCB Biopharma wanted to offer a solution enabling scientists to "self-service" research data rapidly with the aim to accelerate the early discovery process.

○ Scientists define the data set that is relevant to their investigation in a ‘data collection & preparation’ tool, execute the resulting query against SingleStore, and visualize it in a data-analytics tool.

○ Data alerts are generated with the help of SingleStore queries to inform end-users about the arrival of fresh information.

UCB selected SingleStore for raw query performance and for concurrency. we serve on a daily basis between 220-800x scientists in several countries.

  • Query performance execution
  • Concurrent users
  • Simplified data pipeline
  • Metrics collection/visualization for queries execution.
The availability of high-performance, simple and affordable database technology like SingleStore’s provides an additional accelerator to any data-driven companies.
The cluster has been easily installed, integration is well done (SingleStore studio) - user community is available in case of help and react quickly
Erik Fransen | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Review Source
As a consultant and value-added reseller we position SingleStore at our enterprise customers as a hybrid database solution that can process both operational and analytical real-time workloads at the same time and at scale. Our customer demands for processing any type of data at any location with any analytical tool continue to rise and because existing cloud based platforms often are to complex, costly and limited in terms of multiple services and capabilities, SingleStore fills in an ever growing gap. With SingeStore our customer have access to a high performance, high available, distributed, relational database that can be accessed through standard ANSI SQL. SingleStore supports advanced data pipelines, all relevant data types, on-premise, cloud and hybrid configurations and is completely self-managed. Integrating and processing data from various data sources using data pipelines into the SingleStore database and consequently analyzing the data in high performance in the same database is very effective in terms of minimizing data replications, simplifying analytical processes and overall speed and performance of large operational and analytical workloads.
  • Ease of use (installation, managed service, pipelines)
  • Hybrid configuration (on-premise & cloud), analytical and transactional workload
  • ANSI SQL as a standard
  • Runs on any major cloud platform
  • More use cases needed that have their origin outside the USA
Well suited: high variants in data types and timeliness, large amounts of data, combined analytical and transactional workload, high availability demands, hybrid configurations.

Less appropriate: simple data sets, low volumes.
Score 8 out of 10
Vetted Review
Verified User
Review Source
Before having [SingleStore (formerly MemSQL)] in our organization we used to have SpiCA DB. The challenges being the performance of the DB tends to degrade with the increase in the OLTP significantly over the years. This has resulted in existing DB to perform slow and end customer experience [deteriorated]. Hence a tool was looked for that can improve the performance of the overall E2E flow of transactions and also be scalable to for high level of transactions processing. Currently in our organization [SingleStore] is used as backbone for all the batch data loads and real time messages storing in our line of business. Its success has resulted in pitching in voice to be implemented on other LOB as well.
  • First and foremost with the use of Aggregator master and leaf nodes the query processing time for DB are reduced significantly from hundred of msec to now just below 50msec.
  • Supports very high level of Real time transaction processing, for our project the OLTP via real time messages were ~500 to max of 800 TPS, the SingleStore was able to process those very efficiently with significant lower sever side utilization.
  • One of the most powerful tool for SingleSore monitoring is Planecache query, this helped in measuring performance of the stored procedures and evaluating the optimization required. The use was simple and helped analyst to provide the outcome in shortest interval of time.
  • Features related on [SingleStore (formerly MemSQL)] studio UI for monitoring needed some improvement when we used. The SingleStore studio support team helped us in resolving the issues with relation on running the different sets of indexing queries. Challenges here being the detailed logs were not available and we needed to connect with DBA for more detail drill down.
  • SingleStore can have some more improvement in setting up more examples on help documentation for the beginners and early learners.
SingleStore [formerly (MemSQL)] is very well suited for places
- where the components are processing very large amounts of data and requires very low latency.
- Columnstore compression of data reduces the time to respond. Compression resulted in quick responses which are not achieved using the other DB tools.
- The concept of Rowstore and implementation on frequently used tables results in support of high OLTP.

Not suited/less appropriate
- The In-memory(Rowstore) and col-store does not share the same language compatibility. When required the transition form other table type more efforts are required.
- SingleStore DB (formerly MemSQL) connection between AWS cloud failed when partitioning is higher for data processing.
- Administration is sometime bit confusing when providing layered access to different teams.
Diego Montúfar | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Review Source
We build Data Warehousing solutions for our customers and provide consulting and resell license. [SingleStore (formerly MemSQL)] is a powerful technology which allows to solve most of the toughest data challenges within an organization. Its speed and flexibility makes it a key player in an organization's data innovation.
  • OLAP workloads
  • Fast query responses
  • Multiple use cases in one single database
  • Does not provide adequate support for data discovery apps, i.e. Power BI.
  • It would be great to have a native load balancing component for dealing with aggregator failure. Otherwise having a Child Aggregator becomes optional since not all the customers can afford an external balancing solution and does not feel confortable with switching between aggregators manually.
  • They used to have certifications and training in development and administration. That is very important to have, since other competitors does provide access to those sort of things and although they have free tutorials/videos, that doesn't provide an in-depth understanding.
[SingleStore (formerly MemSQL)] is not good for replacing a complete transactional legacy systems. Migration could be very painful.
It's highly recommended for BI and Analytics use cases though
Jacob Ortega | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
Right now we’re using [SingleStore (formerly MemSQL)] in the whole core platform, we were looking for a database that could handle a huge amount of transactions at the same time without loosing any and have the reliability of writing and storing the records fast so other services can use the data for finalizing the transactions. Also we were aiming to have a product which could be used as a storage solution for Data Scientists and our back office platform.
  • The fastest speed for querying compared with traditional relational database
  • Support JSON and full text search which can be used by API’s
  • Nearly zero admin tasks once it’s running
  • You can use it’s data streaming pipeline with Kafka
  • It doesn’t provide redistribution when you reach the maximum node capacity
  • The Graphical Interface could have a revamp, it’s a little bit laggy
  • You cannot run it local so development should be made always using cloud instances
I think SingleStore [(formerly MemSQL)] should be used in every modern system which needs an analytical tool provided with the database, where performance matters and when you need fast scaling. The database is going to use a lot of resources so if the scenario is cost sensitive then perhaps is not the best solution in terms of infrastructure.
Darrin Thompson | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
We use it to power a custom reporting and analytics solution as part of a larger product offering we sell. It has low enough latency to power impressive dashboards for our end users.

  • Processes large amounts of data with very low latency.
  • The support department is fantastic.
  • The developer experience is lacking. Running developer instances locally requires a lot of RAM.
Low latency analytics or dashboards based on large numbers of records.

Near immediate time from record ingest to availability in large queries.