Accelerate business with instant insights delivered by the world’s fastest database for operational analytics
Scale
Build your data future on a cloud platform made for the demands of the data revolution
Handle Hybrid Workloads
Ability to handle highly concurrent OLTP and OLAP (Hybrid) workloads in a single system
Overview
MySQL
Description
Built for maximum ingest, fast query, and high concurrency to help you process, analyze, and act on data instantly. Available in the cloud, on Kubernetes, or on-premises.
Single server database that can be run in a cluster with limited scalability. MySQL stores data on disk and is often used with a caching layer.
Database Model
Relational DBMS
Relational DBMS
DBaaS Offering
SingleStore Helios
MySQL Database Service
Real-Time Analytics
Data Ingest
"The first database with true linear shared-nothing scalability, enabling essentially unlimited scale, proven from three leading industry benchmarks: TPC-C, TPC-H, and TPC-DS."
Architecture is not designed to handle analytics on rapidly changing real-time data.
5 / 5
1 / 5
Manageability
Maintenance
Rapidly deploy the integrated software only environment on standard hardware for dramatically less complexity and manageability.
Requires a lot of manual efforts to maintain and manage the routine cluster operations.
5 / 5
3 / 5
Deployment and Administration
Flexibility
Devops enabled for rapid deployment, scale, on multi-cloud. Open platform runs with Kafka, Spark, HDFS, Kubernetes.
Upgrades are really painful. Extensive tooling support for devops is only available on the enterprise edition.
5 / 5
3 / 5
Scalability
Architecture
Scale-out architecture efficiently and quickly responds to growing workloads leveraging commodity hardware without add-ons or specialized tuning expertise.
Cannot scale-out well due to their single box architecture.
5 / 5
2 / 5
Performance
Data Ingest
Ingesting streaming data in parallel with exactly-once semantics for direct, immediate processing or raw data & events from sources such as Kafka, Spark, S3 and data formats such as Parquet, JSON, and CSV. Common batch load methods are also supported.
Doesn't offer code generation and skiplist indices so as to offer optimal query performance for real-time analytics.
Watch this video to learn how SingleStore works and why customers use it.
Customer Success
SingleStore is Trusted by The World’s Top Brands
Tapjoy
60,000 Concurrent Queries per Second Across a Single Cluster
Real-time mobile ad optimization and overlap targeting analysis
“Working with SingleStore, we gain an unprecedented advantage in real-time analytics, delivering effective models for our partners to increase engagement rates and boost revenue.”
— David Abercrombie, Principal Data Analytics Engineer
With SingleStore, Medaxion has found a solution to the analytics problems that plague companies across the health care sector and beyond.
“By combining the ease of presentation and abstraction of Looker for analytics, with the technical prowess of SingleStore as the database behind Looker, we now have simply the best analytics in healthcare.”
