The Real-Time Data Warehouse
for the Front Lines of Your Business

MemSQL is the real-time data warehouse you can run anywhere that ingests millions of events per second while analyzing petabytes of data for instant time to insight.

real-time data warehouse

Streaming Data Ingest

Easy to setup real-time data pipelines with exactly-once semantics

Live Data

Memory optimized tables for analyzing real-time events

Historical Data

Disk optimized tables with up to 10x compression and vectorized queries for fast analytics

Product Overview

real-time database
Ingest
Retain
Analyze
Deploy

Real-Time Data: Live data from operational applications or web services



Real-Time Data

Apache Kafka and Spark: Streaming data from real-time message and transformation queues



Kafka or
Spark

Historical Data: Import from archive, data lake or block storage sources such as HDFS and Amazon S3

Historical Data

Applications: Embed custom visualizations and reports for analytic applications

Applications

Dashboards: Build dashboards and run ad hoc queries with industry standard business intelligence tools

BI Dashboards

Fully Managed Cloud: Fully managed cloud service on Amazon Web Services or Microsoft Azure

Fully Managed Cloud

Self Service Cloud: Amazon AWS, Microsoft Azure, Google Cloud Platform

Self Service Cloud

On-Premises: Configure as a private cloud on industry standard hardware

On-Premises

MemSQL Pipelines: Real-time ingest from Apache Kafka or Amazon S3 with exactly-once semantics and native management UI



Streaming Ingest

Live Data: Memory optimized tables for analyzing real-time events



Live
Data

Historical Data: Disk optimized tables with up to 10x compression for analyzing historical datasets



Historical
Data

MemSQL is a scalable real-time data warehouse that ingests data continuously to perform analytics for the front lines of your business. Ingest and transform millions of events of data per day while simultaneously analyzing billions of rows of data using standard SQL. Query traditional SQL, JSON and Geospatial data types in real time.

real-time ingest

Real-Time

Power analytics for operational applications, ad-hoc queries and dashboards that require ultra fast data ingestion and low latency queries with high user concurrency

scale-out

Scalable

Easily analyze up to petabytes of data and support millions of users on scale-out industry standard hardware for fast highly available results

multi-cloud

Multi-Cloud

Deploy on-premises, in the cloud or as a service including drop-in compatibility with existing middleware, integration and Business Intelligence tools

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Make the Right Choice. Yours.

run anywhere

Span from on-premises to the cloud for added flexibility and performance Learn More

managed service

Fully Managed Cloud

Fully managed cloud service on Amazon Web Services or Microsoft Azure provides hardware, software, and management services with hourly or annual subscription

self service cloud

Self-Service Cloud

Self-manage MemSQL on leading public clouds including Amazon Web Services, Microsoft Azure, or Google Cloud Platform

on-premises

On-Premises

Deploy on-premises utilizing best practice architecture to maximize current infrastructure investments

Fast Data Ingest for Fast Results

real-time data ingest
08:52:01252 msSucceeded164164164
08:52:11336 msSucceeded101101101
08:52:34396 msSucceeded124124124
08:52:26301 msSucceeded290290290
08:52:56312 msSucceeded164164164
08:52:68282 msSucceeded124124124
08:52:13309 msSucceeded116116116
08:52:37310 msSucceeded145145145
08:52:23307 msSucceeded157157157
08:52:81398 msSucceeded183183183

Connect MemSQL with your data ecosystem across streaming, batch load, and application environments so you can analyze your live and historical data in a single scalable system.

create pipeline

Create PipelineFEATURED

Natively define streaming data ingest from Apache Kafka and Amazon S3 with a single command

exactly-once semantics

Exactly-Once SemanticsFEATURED

Achieve guaranteed message delivery of streaming data for accurate reporting and analysis

import data

Data Import

Import from relational databases or cloud storage systems using native data load functions

streaming inputs

Streaming Inputs

Apache Kafka, Apache Spark

database inputs

Database Inputs

MySQL, SQL Server, Oracle, Postgres, Teradata, Redshift

storage inputs

Storage Inputs

Amazon S3, HDFS

Build Powerful Analytic Applications

low latency

Achieve ultra fast query response on live and historical data using ANSI compliant SQL.

sophisticated insignts

Sophisticated Insights

Perform ad hoc analysis with business intelligence tools, run machine learning algorithms for real-time scoring, perform geoanalytic queries in real-time

geospatial

Geospatial SupportFEATURED

Store, query, and index geographic data types including polygons and points to support area, distance, location analytics in real-time

JSON

JSON OptimizedFEATURED

Store and query JSON data as a column-type to efficiently store and analyze multi-attribute objects

multi-statement transactions

Multi-Statement Transactions

Multi-statement transactions allow a set of DML statements to be combined into a single transaction

compiled queries

Compiled Queries

Repeat queries are compiled into low level machine code to deliver record breaking response for analytic queries

distributed joins

Fully Distributed Joins

Scale out fully distributed JOINs across any table and column for simple efficient query access

Durable Distributed Storage

The highly scalable distributed system balances data and queries across a cluster of industry-standard hardware for maximum performance, concurrency, and availability

distributed storage

Distributed Storage

Store and process data across clusters of machines for maximize resilience and performance leveraging memory and disk infrastructure

big data capacity

Big Data Capacity

Store petabytes of data on low cost disk and cloud storage for archive requirements while maintaining instant retrieval for fast deep analysis

massivelly parallel

Massivelly Parallel

Scale out shared nothing architecture to provide a robust parallel execution engine for read and write queries delivering ultra-fast performance

full durability

Full Durability to Disk

Write transactions directly to disk or write to memory with full data persistence and archiving

in-memory performance

In-Memory or On-Disk Tables

Use memory for transactional workloads and cleanup while using disk for historical data and analysis

compressed tables

Compressed On-Disk Tables

Column store disk compression optimizes resources for storing up to petabytes of data

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Simple Unified Management

database management

MemSQL Ops is a simple and powerful web interface for MemSQL cluster information, configuration, deployment, and monitoring.

performance monitoring

Monitor Performance and Capacity

Proactively respond to issues and ensure your MemSQL cluster is always online, operating within server capacity, and optimally performing

deploy

Provision and Deploy

Specify your cluster hosts, and MemSQL Ops will provision and deploy MemSQL according to your desired cluster configuration

high availability

High Availability

MemSQL holds a redundant copy of data to protect against data loss. Online replication ensures data consistency

cluster management

Cluster Management

Automate and simplify common tasks including adding, dropping, restoring, rebalancing partitions

scaling

Administration and Scaling

Manage data replication, along with backups and restore without pausing or going offline

data center replication

Cross Data Center Replication

Synchronize one cluster with another over a broad network connection

Robust Enterprise Security

Meet or exceed data security requirements without compromising database performance. Easily manage how users and roles access data to meet intensive workloads for web scale or regulated environments.

RBAC

Role-Based Access Control (RBAC)

Efficiently manage simple or robust security configurations by user role and group while maintaining maximum performance

encryption

Encryption

Data encryption is supported at time of ingest and when delivered across nodes using SSL. Use third party storage encryption while data is stored in MemSQL

Audit Logging

Audit Logging

Database logging writes all activities to a secure external location to support information security tasks such as tracking user access, investigating suspicious activities and validating access control policies

authentication

Authentication

Manage existing account access with PAM (Pluggable Authentication Module) and SAML authentication support

Integrate With The Modern Data Ecosystem

Leverage the MySQL wire protocol or JDBC/ODBC interface to integrate with existing middleware or technology investments

Deploy

Cloud
Amazon Web Services, Microsoft Azure or Google Cloud Platform

On-Premises
Deploy on virtualization and container services like Docker and VMware

Ingest

Relational
Oracle, SQL Server, MySQL, Postgres, Teradata, SAP, and more

Streaming
MemSQL Pipelines, Apache Kafka, Amazon S3, HDFS, Apache Spark

Analyze

Query
ANSI SQL, JSON, Geospatial

BI Tool
Tableau, Looker, Zoomdata, and Microstrategy

Ready to Get Started?

Take your business real-time