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SingleStore

SingleStore
Formerly MemSQL

Overview

What is SingleStore?

SingleStore aims to enable organizations to scale from one to one million customers, handling SQL, JSON, full text and vector workloads in one unified platform.

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Learn from top reviewers

Awards

Products that are considered exceptional by their customers based on a variety of criteria win TrustRadius awards. Learn more about the types of TrustRadius awards to make the best purchase decision. More about TrustRadius Awards

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Pricing

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OnDemand

$0.69

Cloud
per hour

Entry-level set up fee?

  • Setup fee optional
For the latest information on pricing, visithttps://www.singlestore.com/pricing/

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting/Integration Services
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Product Details

What is SingleStore?

SingleStore enables organizations to quickly and easily scale from one to one million customers, handling SQL, JSON, full text and vector workloads in one unified platform.

SingleStore Features

  • Supported: Vector database
  • Supported: Transactions (OLTP)
  • Supported: Analytics (OLAP)
  • Supported: SQL
  • Supported: JSON
  • Supported: Real-time

SingleStore Videos

SingleStore NOW 2024: Outreach / AI- and Data-Driven Sales
SingleStore Now 2024 / Snowflake + SingleStore: Better Together
SingleStore NOW 2024: Adobe / What’s New in SingleStore: AI in Production
SingleStore Now 2024: AWS / Enterprise AI Innovation: Gen AI Experimentation
SingleStore Now 2024: 6sense / AI in Production: Lessons Learned
SingleStore Now 2024: LlamaIndex / Building Multi-Agent RAG Systems
SingleStore NOW 2024 / LiveRamp: Building the World’s Largest Identity Graph without a Graph DB
SingleStore Now 2024: SAS + SingleStore = Enterprise AI at Scale
SingleStore Now 2024 / Pyler: AI-Powered Brand Safety
SingleStore Now 2024: Groq / AI Trends, and Running LLMs in the Enterprise
SingleStore Now 2024: AI with SingleStore, IBM StreamSets and watsonx.ai

SingleStore Integrations

SingleStore Technical Details

Deployment TypesOn-premise, Software as a Service (SaaS), Cloud, or Web-Based
Operating SystemsLinux
Mobile ApplicationNo
Supported CountriesGlobal
Supported LanguagesEnglish

Frequently Asked Questions

SingleStore aims to enable organizations to scale from one to one million customers, handling SQL, JSON, full text and vector workloads in one unified platform.

Oracle Database, Microsoft SQL Server, and MongoDB are common alternatives for SingleStore.

Reviewers rate Performance highest, with a score of 9.2.

The most common users of SingleStore are from Small Businesses (1-50 employees).
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Comparisons

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Reviews From Top Reviewers

(1-5 of 68)

MemSQL is Great for Use Cases where Performance (Latency and Data Freshness) Needs are High

Rating: 9 out of 10
September 01, 2021
Vetted Review
Verified User
SingleStore
2 years of experience
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.
Cons
  • 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.

SingleStore, the technology you want to have to accelerate your data innovations

Rating: 10 out of 10
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
Cons
  • 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

SingleStore: An excellent compute engine

Rating: 8 out of 10
February 23, 2024
Vetted Review
Verified User
SingleStore
2 years of experience
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.
  • Computation
  • Sharded infrastructure
  • Query optimization tools/AI Assistants
Cons
  • Granular user-permissioning in the online UI
  • More robust server-level telemetry data
  • Easier to access/use database log information
SingleStore is excellent at computing heavy workflows. The column-store table design combined with efficient sharding strategies make for a beast of a database that lets you compute large queries at ease. Singlestore also offers a variety of developer tools such as SQrL (their AI assistant) and their Query Profiler, which are massively helpful for figuring out what bottlenecks exist in a given query.

SingleStore provides for customer-facing internal users but fails for production usage

Rating: 8 out of 10
August 30, 2021
Vetted Review
Verified User
SingleStore
1 year of experience
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.
Cons
  • 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.

Good Analytics Database.

Rating: 8 out of 10
January 09, 2025
Vetted Review
Verified User
SingleStore
2 years of experience
We use a single store for an analytics use case in our organization. The previous database was not distributed, and scaling issues were occurring, so a single store with a distributed nature helped us solve this issue. We mainly use the columnar tables in a single store for analytics.
  • Sharding/Distributed Database.
  • Analytics Queries.
  • Good Observability.
Cons
  • Row tables.
  • Query Profiler.
In my opinion, it is well suited for analytics use cases. However, it is less appropriate for transactional data as row tables are saved in memory, and single nodes are more costly than traditional databases.
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