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 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.

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 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.

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

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.

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).

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.

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.

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.

I am exploring SingleStore as a personal interest to learn new tech skills.

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.

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.

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.

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!