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Filter 21 vetted SingleStore (formerly MemSQL) reviews and ratings
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December 16, 2020
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.
December 15, 2020
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
December 09, 2020
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.
We are using the SingleStore product in our data delivery department which serves the whole company and its client base. The problem we use this for is to address data latency issues between the transaction stores and the dashboards customers monitor for progress on their advertising campaign fulfillment.
- It excels at providing operational store view of data which addresses latency issues
- Its scalability is great
- The query performance is also a notable plus for the tool
- We are still new users of the tool and don't have strong recommendation in this matter yet.
December 02, 2020
We use it to hold and query real estate listings in four states. This is the engine behind our website's and mobile app's main feature - property search. The queries have geospatial criteria. Because of the volume of records and complexity of queries, MemSQL was an obvious choise for it's performance. Now, as SingleStore offers collumnar storage, we can use it for other things like analytics and reporting.
- Scaling - columnar storage makes it easy to scale without cost or signifigant performance hits
- Speed - where performance is an issue, we can keep the data in RAM
- Simplified management - Love MemSQL's web UI to manage clusters
- I'm fine here - I think Single store is addressing needs (Managablility, Flexible maintenance windows, responsive tech support) nicely
- I suppose reliability is an issue. I see the few causes behind this get fixed quickly and the platform becomes more dependable as it matures
SingleStore DB (formerly MemSQL) is currently being used as the MPP DB for our data lake. We use it to ingest different information from the operational platform in order to enable it for app development and analytics. Using SingleStore DB (formerly MemSQL) allowed us to process a high volume of data since it has scalability by design. Memory management in SingleStore DB (formerly MemSQL) is very efficient and even on an infra level the cluster management is straightforward.
- High data volume processing.
- Operational data enablement.
- Redistribution when a node is full.
- Split processing data usage from data volume license.
December 16, 2020
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.
December 03, 2020
We are using SingleStore for analytical data processing workflow with [a] huge volume of columnar data set. Recently we started utilizing rowstore for real-time data processing. One thing is evident that SingleStore is really fast for similar data processing conditions compared to competitions. During our journey of adopting SingleStore, we also faced some challenges. We hope that SingleStore [will] be supported on AWS ECS containers. Overall, nice data solution [and] really fast data processing.
- Columnstore compression of data is awesome. Sometimes we got 85+ % compression.
- Rowstore is ultrafast.
- Kafka based pipeline is awesome.
- Support for running it on AWS ECS containers.
December 04, 2020
We use [SingleStore] [(formerly MemSQL)] to address the ingestion of fast data streams and to answer analytical queries with tight timeout requirement.
- Fast analytical queries with in-mem and on-disk columnar store.
- Scale out capability
- Good dashboard for managing the cluster
- Licencing model needs to be more flexible, users need to be able to do pay-as-you-go
- Data ingestion is still old-style. Integration with e.g., spark lagged behind.
- In-mem and col-store does not share the same language compat. Table type transition is hard.
- HA is no good with 6.0. Recovery time is very long. (and non-predictable)
September 23, 2020
We use SingleStore DB (formerly MemSQL) to store a real-time feed of all kinds of open source data. The data get full-text indexed, stored in start schema, and instantly ready for analysis. Multiple departments have access to multiple dashboards backed up with SingleStore DB (formerly MemSQL).
- Ingesting high volume of data in real-time.
- Excellent query performance (response in milliseconds).
- Feature rich, json support, full-text search.
- Minimum administration is needed.
- Cross-cluster queries
- SingleStore DB (formerly MemSQL) procedural SQL syntax can be simplified
- Materialized views
- Implementing recursion in queries
- Tag cloud generator from a full-text index
February 19, 2020
My overall experience is outstanding. It has excellent performance, and the SingleStore DB (formerly MemSQL) installation is effortless. My expertise in implementing the solution was excellent. Unlimited database feature interface successful Has fast processing prioritize multiple operations Very successful product. It's friendly for MySQL user but faster, more and more. SingleStore DB (formerly MemSQL) has hybrid RowStore and ColumnStore solution to resolve different cases. I was trying to replace MySQL with an in-memory column store SingleStore DB (formerly MemSQL) resolved that issue.
- Data structuring.
- Data retrieval.
- GUI needs to be better.
- To scale out on the fly needs to be a little simpler.
August 02, 2016
SingleStore DB (formerly MemSQL) is used as a persistent storage solution for Spark. We use SingleStore DB (formerly MemSQL) spark connector (Scala code) to bridge two techs. I am leading projects of using spark and SingleStore DB (formerly MemSQL) to process life science data. It solved the spark storage issue.
- Faster query speed than traditional SQL database.
- It con server in the pipeline to deal with streaming data with Kafka, spark streaming and SingleStore DB (formerly MemSQL).
- It is very scalable.
- Better tuning of SingleStore DB (formerly MemSQL) performance on Scale-up server
- SingleStore DB (formerly MemSQL) connection between spark failed when more than around 48 partitions data processing
- Provide faster python API for invoking SingleStore DB (formerly MemSQL)
SingleStore (formerly MemSQL) Scorecard Summary
What is SingleStore (formerly MemSQL)?
SingleStore, formerly known as MemSQL, provides one platform for all data, built so users can engage with insight in every moment. Used by industry leaders such as Uber, Akamai, Dell EMC, Samsung, and Comcast, SingleStore enables enterprises to adapt to change as it happens, embrace diverse data with ease, and accelerate the pace of innovation. SingleStore is venture-backed and headquartered in San Francisco with offices in Portland, Seattle, Boston, London, Lisbon, and Kyiv. Defining the future starts with The Database of Now™. SingleStore DB is a scalable, distributed SQL system built for modern applications which combines support for transactions and analytics in a single cloud-native, massively scalable architecture for maximum ingest and query performance with the highest concurrency.
SingleStore (formerly MemSQL) Screenshots
SingleStore (formerly MemSQL) Videos (3)
SingleStore (formerly MemSQL) Downloadables
SingleStore (formerly MemSQL) Integrations
Amazon S3 (Simple Storage Service), Zoomdata, a Logi Analytics company, Data Virtuality Pipes
SingleStore (formerly MemSQL) Competitors
SingleStore (formerly MemSQL) Pricing
- Has featureFree Trial Available?Yes
- Has featureFree or Freemium Version Available?Yes
- Has featurePremium Consulting/Integration Services Available?Yes
- Entry-level set up fee?Optional
| Edition | Pricing Details | Terms |
|---|---|---|
| OnDemand | 0.69 | per hour |
SingleStore (formerly MemSQL) Support Options
| Free Version | Paid Version | |
|---|---|---|
| Forum/Community | ||
| FAQ/Knowledgebase | ||
| Social Media | ||
| Video Tutorials / Webinar | ||
| Phone | ||
| Live Chat | ||
SingleStore (formerly MemSQL) Technical Details
| Deployment Types: | On-premise, SaaS |
|---|---|
| Operating Systems: | Linux |
| Mobile Application: | No |
| Supported Countries: | Global |
| Supported Languages: | English |