TrustRadius Insights for SingleStore are summaries of user sentiment data from TrustRadius reviews and, when necessary, third party data sources.
Pros
Real-Time Data Processing Capabilities: Users have consistently praised SingleStore for its efficient real-time data processing capabilities, noting its effectiveness in online transaction processing and big-data batch handling. The seamless integration with external services like Kafka and S3 has also been highlighted as a significant advantage.
Super Fast Data Queries: Reviewers have emphasized the exceptional speed of data queries on SingleStore, enabling them to quickly and efficiently retrieve information for their needs. This feature is seen as a key benefit that enhances overall productivity and decision-making processes.
Scalability and Performance Improvements: Users appreciate SingleStore's scalability for both writes and reads, along with notable performance enhancements. These include faster request processing rates, improved algorithm processing times, and the ability to handle growing workloads without compromising efficiency or reliability.
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SingleStore Reviews
18 Reviews
Mid-sized Companies (51-1,000 employees)
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I use SingleStore for the data warehouse of a fintech, which processes payments through TCs worldwide. The integration was with Azure DataFactory, without complications, it helps us in an excellent way since we are very fast in obtaining the data for our dashboards and additionally the compression of the information.
Utilizo SingleStore para el datawarehouse de una fintech, la cual procesa pagos mediante TCs a nivel mundial, la integracion fue con Azure DataFactory, sin complicaciones, nos ayuda de manera excelente dado que tenemos mucha rapidez en obtener los datos para nuestros dashboards y adicional la compresion de la informacion
Pros
Fast Data Recovery
Data compression by 80%
Having the information in sheets, which helps to process the information quickly
Simplicity in TSQL
Recuperacion de Datos de manera rapida
Compresion de datos en un 80%
Tener la informacion en hojas, lo que ayuda a procesar la info rapidamente
Simplicidad en TSQL
Cons
Azure pipelines do not have many parameterization features compared to others, for example AWS.
Error handling, for example when it fails due to memory, only indicates that but not exactly in which process it fell.
a more detailed profiler
Direct purchase through partners, but buying directly from the brand, I think, would be better without intermediaries.
los pipelines para Azure no tienen muchas caracteristicas de parametrizacion en comparacion con otros, ejemplo AWS
El manejo de errores, por ejemplo cuando falla por memoria solo indica eso pero no exactamente en que proceso cayo
un profiler mas detallado
la compra directa a travez de partners, sino comprar directo a la marca creo que seria de mejor manera sin intermediarios
Likelihood to Recommend
I think it is very useful for managing information for business intelligence processing, given that the information that is brought is done quickly, therefore when loaded into the dash it is processed correctly. In addition, for large companies the cost would be significant. The cloud service is good.
Pienso que es bien util para el manejo de informacion para procesamiento de business intelligence, dado que la informacion que se traer es de manera rapida, por ende al cargar en los dash esta se procesa de manera correcta, adicional para grandes empresas el costo seria significativo, el servicio de nube es bueno
This review was originally written in Spanish and has been translated into English using a third-party translation tool. While we strive for accuracy, some nuances or meanings may not be perfectly captured.
We use SingleStore for a super fast client experience, running real time analytics on billions of events arriving every day from various publishers channels.
Pros
Performance - Milliseconds response of 80 tables Joined queries
Scalability - Ability to grow with no downtimes
Client success - Attentive to business needs, deep level support, patches and fixes
Efficiency - Built-in Kafka / S3 / MySQL integrations well adjusted to leverage SingleStore architecture and hardware
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Cons
Add Iceberg tables / files Pipeline
CDC out in form of logfile / binlog / producer to Kafka
Efficiency with multi shard-key use case: Joined three tables when one of them holds both shard keys of the other two.
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Likelihood to Recommend
SingleStore shines as a unified solution of high OLTP & OLAP workloads. The technology suits big data systems with mutual identity (shard key/s), fast JSON processing, vector search for AI features and streaming.
The client success attentiveness and the consistent support of experts in any matter shows the company maturity and their vision for success. No doubt this is a long term partnership.
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.
Pros
MySQL Integration/Wire
Self-Managed Solution
Analytical Query Speeds
Ability to perform Translytical Queries
Cons
Lower price plans for their paid solution
A longer period of time to use the free credits
More Node support within self-managed
Likelihood to Recommend
SingleStore is a phenomenal solution and replacement to MySQL/MariaDB. Being able to instantly start using it without any prior experience is fantastic, as other solutions required learning new syntax which slows development.
In addition, SingleStore offers many opt-in features such as Rowstore rather than being obliged to use it. I believe it’s better to use features as needed, rather than being forced to dive in and deal with learning things.
One of the biggest factors to what drew me to SingleStore was the self-managed option, being a startup at the time we didn’t want to pay for a solution. We still use the self-managed option 2 years later, and couldn’t imagine using anything else.
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.
Pros
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
Likelihood to Recommend
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.
VU
Verified User
Employee in Information Technology (51-200 employees)
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.
Pros
Delivering thousands of records at blazing fast speeds
full text search
scaling
Cons
Improved UI for their portal
Better ticket system
More workers on workspace
Likelihood to Recommend
Reliable, scales and you can do full text search across the data. Customer support ticketing system could be improved but it's barely a con
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
Pros
Real-time data processing
Online transaction processing
Big-data batch handling
Integration with external services (Kafka, S3, etc.)
Super fast data queries
Cons
While improving, backup is still hard to configure
Pricing of self-hosted instances
Few external documentation resources
Likelihood to Recommend
I would recommend SingleStore for use cases where a relational database is needed for handling both online transaction processing (OLTP), online data streaming, and batch big-data processing. Since it supports both in-memory and disc-based tables, it is suitable for handling large tables as well as smaller, fast ones. SingleStore is MySQL compatible in terms of connection so you could use it with any connector that supports MySQL, and is mostly TSQL compatible so if you come from Transact-SQL background the switch will be simple. While supporting JSON and document datatypes, I would not use SingleStore as a main document database, as its strengths lay in the relational realm.
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.
Cons
Usability
Reliability and Availability.
Performance
Pros
Scalability on demand.
Near real time performance.
Easy query profiling.
Likelihood to Recommend
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 to transfer 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 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.
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
Cons
Data ingestion from JDBC sources
More robust and easy to use Integration with tools like spark
More options for setting up and doing PoC with singlestoreDB
Pros
Data ingestion from object stores
Storing data in row and columnar store
Data ingestion from S3 to singlestoreDB takes 6secs for 550K records with 30 columns
Likelihood to Recommend
singlestoreDB can be used for both staging data and creating marts on which ML algorithms can be run. The most interesting part is their pipeline function which allows really fast and consistent ingestion of data. And setting up these pipelines is really easy with configurations for sources system creds.
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
Cons
open many SQL Editor in same time
wizard for object creation (table, view, procedure...)
link table from other database
Pros
super fast
execute complex query
the use of several types of database
availablity
sclability
Likelihood to Recommend
It can be used on any need for data treatment: • Development • data analysis • migration preparation • for data processing•......
VU
Verified User
Engineer in Information Technology (201-500 employees)
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.
Pros
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
Cons
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
Likelihood to Recommend
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.
