DBMS > SingleStore vs. StarRocks vs. TimescaleDB vs. Yanza

System Properties Comparison SingleStore vs. StarRocks vs. TimescaleDB vs. Yanza

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Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

Relational DBMS

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

Score	5.60
Rank	#62	Overall
	#35	Relational DBMS

Score	1.04
Rank	#189	Overall
	#88	Relational DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

www.singlestore.com

www.starrocks.io

www.timescale.com

yanza.com

Technical documentation

docs.singlestore.com

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

docs.timescale.com

Developer

SingleStore Inc.

The Linux Foundation

since Feb 2023

Timescale

Yanza

Initial release

2013

2020

2017

2015

Current release

8.5, January 2024

2.5.3, March 2023

2.15.0, May 2024

License

Commercial or Open Source

commercial

free developer edition available

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

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++, Go

C++, Java

Server operating systems

Linux

64 bit version required

Linux

Linux
OS X
Windows

Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

but no triggers and foreign keys

yes

full PostgreSQL SQL syntax

APIs and other access methods

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

JDBC
MySQL protocol

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP API

Supported programming languages

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

Java

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

user defined functions

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

hash partitioning

horizontal partitioning (by range and hash)

yes, across time and space (hash partitioning) attributes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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

Source-replica replication with hot standby and reads on replicas

none

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

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

In-memory capabilities

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

yes

User concepts

Access control

Fine grained access control via users, groups and roles

Role based access control and fine grained access rights

fine grained access rights according to SQL-standard

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

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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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

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

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24 January 2024, Business Wire

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provided by Google News

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21 December 2023, Pulse 2.0

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14 February 2023, VentureBeat

StarRocks Brings Speedy OLAP Database to the Cloud
14 July 2022, Datanami

StarRocks launches managed DBaaS for real-time analytics
14 July 2022, InfoWorld

StarRocks' real-time analytics engine moves to the cloud
14 July 2022, SiliconANGLE News

provided by Google News

TimescaleDB Is a Vector Database Now, Too
25 September 2023, Datanami

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4 April 2024, PR Newswire

Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL
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Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data
22 February 2022, Business Wire

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31 July 2019, DataDrivenInvestor

provided by Google News

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