DBMS > Rockset vs. SingleStore vs. STSdb vs. VoltDB

System Properties Comparison Rockset vs. SingleStore vs. STSdb vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

A scalable, reliable search and analytics service in the cloud, built on RocksDB

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Secondary database models

Relational DBMS
Search engine

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.79
Rank	#211	Overall
	#35	Document stores

Score	5.60
Rank	#62	Overall
	#35	Relational DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

rockset.com

www.singlestore.com

github.com/STSSoft/STSdb4

www.voltdb.com

Technical documentation

docs.rockset.com

docs.singlestore.com

docs.voltdb.com

Developer

Rockset

SingleStore Inc.

STS Soft SC

VoltDB Inc.

Initial release

2019

2013

2011

2010

Current release

8.5, January 2024

4.0.8, September 2015

11.3, April 2022

License

Commercial or Open Source

commercial

free developer edition available

Open Source

GPLv2, commercial license available

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

C++

C++, Go

Java, C++

Server operating systems

hosted

Linux

64 bit version required

Windows

Linux
OS X

for development

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

dynamic typing

yes

primitive types and user defined types (classes)

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

ingestion from XML files supported

Secondary indexes

all fields are automatically indexed

yes

SQL

Support of SQL

Read-only SQL queries, including JOINs

yes

but no triggers and foreign keys

yes

only a subset of SQL 99

APIs and other access methods

HTTP REST

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

.NET Client API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

Bash
C
C#
Java
JavaScript (Node.js)
Python

C#
Java

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

Java

Triggers

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

hash partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

stores two copies of each physical data partition on two separate nodes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

FOREIGN KEY constraints are not supported

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

yes

Snapshots and command logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users and organizations can be defined via Rockset console

Fine grained access control via users, groups and roles

Users and roles with access to stored procedures

More information provided by the system vendor

Specific characteristics

SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» more

Competitive advantages

SingleStore’s competitive advantages include: Easy and Simplified Architecture with...
» more

Typical application scenarios

Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more

Key customers

IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more

Market metrics

Customers in various industries worldwide including US and International Industry...
» more

Licensing and pricing models

F ree Tier and Enterprise Edition
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

Turbocharge Your Application Development Using WebAssembly With SingleStoreDB
17 October 2022, Akmal Chaudhri, SingleStore (sponsor)

Cloud-Based Analytics With SingleStoreDB
9 June 2022, Akmal Chaudhri, SingleStore (sponsor)

SingleStore: The Increasing Momentum of Multi-Model Database Systems
14 February 2022, Akmal Chaudhri, SingleStore (sponsor)

show all

Recent citations in the news

Honing business data with AI real-time analytics
14 March 2024, SiliconANGLE News

Rockset Announces 2024 Index Conference, Industry Event for Engineers Building Search, Analytics, and AI ...
18 April 2024, Datanami

Rockset targets cost control with latest database update
31 January 2024, TechTarget

Rockset Releases New Instance Class, Gains Momentum as the Search and Analytics Database Built for the Cloud
31 January 2024, GlobeNewswire

Real-time analytics database provider aims to cut compute costs by 30%
31 January 2024, SDxCentral

provided by Google News

SingleStore CEO sees little future for purpose-built vector databases
24 January 2024, VentureBeat

Building a Modern Database: Nikita Shamgunov on Postgres and Beyond
17 April 2024, Madrona Venture Group

SingleStore Announces Real-time Data Platform to Further Accelerate AI, Analytics and Application Development
24 January 2024, Business Wire

SingleStore adds indexed vector search to Pro Max release for faster AI work – Blocks and Files
29 January 2024, Blocks & Files

SingleStore, Snowflake Help Customers Build Enterprise-Ready Generative AI Apps
3 January 2024, Acceleration Economy

provided by Google News

Unveiling Volt Active Data's game-changing approach to limitless app performance
16 October 2023, YourStory

VoltDB Launches Active(N) Lossless Cross Data Center Replication
31 August 2021, PR Newswire

VoltDB Turns to Real-Time Analytics with NewSQL Database
30 January 2014, Datanami

VoltDB Upgrades Power, Security of Its In-Memory Database
1 February 2017, eWeek

VoltDB Aims for Fast Big Data Development -- ADTmag
29 January 2015, ADT Magazine

provided by Google News

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