SingleStore

Formerly MemSQL

We are using SingleStore database as our main database in both production and non-production workloads. We are using both memory-based tables and disc-based tables (AKA column-store) and can easily join and query all tables. Our use of SingleStore is for many diverse business use cases, ranging from online data streaming, OLTP, and big-data batch processing.
SingleStore proved to be an excellent business and technical partner, with a top-of-line technical product and good business and technical support. Support is provided either directly from the supplier or from SingleStore's trusted partners

We recommend SingleStore to our customers who face scalability issues with their OLTP or OLAP systems. Many companies use database engines that are inappropriate for specific data computing tasks. For example, MySQL is not meant for analytics or real-time analytics. SingleStore is.
SingleStore compresses data, which lowers your disk footprint, thus saving storage costs.
Most of the time, we'll do a discovery about our customer pain points and determine if SingleStore is the right fit. We'll then work with SingleStore to do a POC to ensure we meet all customer requirements.

We use it as our main database solution. We use it to query large datasets in large analytical queries.

We use SingleStore to ingest, store, and process data from our hardware player trackers. The challenge is the amount of data (hundreds of millions of rows) and being able to query it quickly.

We use SingleStore for our various web apps. We were previously using AWS RDS which was slowing things down as we added more data and added more analytics, queries, and data enrichment tasks. Moving to SingleStore removed all of those bottlenecks.

At Tebex we use SingleStore to power our game analytics SaaS. SingleStore is used to power our translytical queries, given that we solely rely on one database solution. We have investigated numerous solutions in the past, which have all required running multiple database solutions in parallel. One for transactional queries and the other for analytical queries. This makes foreign keys impossible to work with, in addition to opening up to multiple points of failure if things were to go wrong. Our use case at Tebex is to give in-game creators the ability to get a better view into their game server analytics. SingleStore makes this process very easy, and the MySQL wire integration has made working with SingleStore a lot easier than the competitors we looked at.

FLOWD uses SingleStore as its data store for water usage readings. It needs to deal with the ingestion of hundreds of water monitoring devices and provide real time analytics to users.

SingleStore is used as source of truth for our data. It is one of our main database providers. Singlestore acts as a 1) historical ledger for granular log level data, as well as 2) a compute engine for deriving new metrics. Our use-cases for SingleStore span various environments including production, test, UAT, & development.

We use it as our analytical database. It is more reliable and faster than our previous vendor. It also allowed us to replace another service that frees up $1500/month. We retrieve thousands of records at a time quickly.

We felt that running queries on BigQuery for every query is really slow, especially from an user point of view. After seeing the drastically improved latency of SingleStore we decided to use to solve this issue. We currently use it to run low volume queries for a much faster response, significantly improving user experience.

We use SingleStore for all our database needs. We rely on it to store terabytes of data and do complex analytical queries very quickly.

The app we've built at Particl runs large analytical queries, and requires the ability to ingest large amounts of data 24/7. Most other services we looked into were not able to handle our analytical queries, or could not ingest the data quick enough. SingleStore has resolved this issue, which is mission critical.

In our data-centric organization, SingleStore is integral for managing, processing, and analyzing vast amounts of data in real-time, enhancing our ability to serve dynamic insights to end-users. It adeptly addresses the critical need for speed and scalability in data operations, enabling swift data queries and seamless infrastructure expansion without sacrificing performance. Our application of SingleStore spans various functions, from operational systems to advanced analytics, facilitating a unified data view that supports coherent business strategies. Its real-time processing capabilities allow us to offer personalized user experiences, such as tailored recommendations and instant analytics dashboards. SingleStore's role is not just in data management; it's a catalyst for leveraging data as a strategic asset, fostering innovation and driving efficiency across our organization, thus aligning with our growth and evolving business needs.

My team and I have engaged with SingleStore, discussing the potential use of their database in our newly developed application. In collaboration with the SingleStore team, we conducted a POC to show the advantages of using SingleStore in our application.

We are using SingleStore as a DBMS. We wanted fast engine which reflects the data on portal immediately for better user experience. Also there were couple of use-cases where we wanted capability of transactional and real-time analysis. And SingleStore has fulfilled this requirement in my organization as it has capability of fast ingest and high-performance queries.

SingleStore is the primary Database we use in our org. It powers all our use cases which include insights , dashboards and journeys in our customer's pages. We use SingleStore to pretty much store everything and retrieve a huge volume of data in near real time without experiencing any downtime. It has an excellent interface which makes it much better tool than others

We use it as our application database and have a tremendous performance impact since we are using SingleStore. We also like how it has developed and what future benefits it will offer.

We use SingleStore as the primary database for our Digital Marketing OS. It allows us to process transactions and answer complex analytical queries within the same database.

We use SingleStore to manage a large and complex analytical workload for multiple financial customers. SingleStore is the database behind our real-time user interface. SingleStore also hosts our dashboards that display a mixture of data computed dynamically at the time of display and pre-computed values generated when data is ingested. Our software allows users to track the performance of retirement plans, and to compare data across plans. Many of these operations are data-intensive and we've been able to roll out many new and often compute-hungry features since switching to SingleStore two years ago.

I was doing some data engineering for this one client, and I thought that migration would take up to two weeks. In the end, thanks to Single store I was able to get everything done in less than an hour! The learning curve was incredibly easy, and incredibly well documented!

We are an analytics SaaS product and currently use Singlestore as our primary database. Customer data from different sources - website, ad platforms, CRM are streamed into singlestore and our end users can directly query this data from our web application. Queries are run against the singlestore database which helps us in streamlining the ingestion and analytical use cases.

The core business problems being solved by Singlestore are - having a unified database for customer data, running low latency queries and serving responses within tight SLAs to our clients

We have a lot of queries for analyzing data about student engagement and courses chosen and bought; we need to get future trends by combining our data with the data coming from open sources and bought. Most problems are related to the processing of big volumes of data and presenting it using tableau and power bi dashboards.

We use singlestoreDB as our landing storage for our product. Our product provides insights in data and quality of data. For that we require fast ingestion feom sources like S3, GCS and Azure Blob. We extensively use singlestoreDB's PIPELINE function for ingesting data into SingleStoreDB. We ran our ML algorithms on the data stored on singlestoreDB. Which gave us really good results and helped optimize our algorithms by using some of its inbuilt features

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.