DBMS > EventStoreDB vs. RocksDB vs. SingleStore vs. SwayDB vs. TimescaleDB

System Properties Comparison EventStoreDB vs. RocksDB vs. SingleStore vs. SwayDB vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

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 embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

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

Primary database model

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	1.10
Rank	#179	Overall
	#1	Event Stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	5.60
Rank	#62	Overall
	#35	Relational DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

Technical documentation

developers.eventstore.com

github.com/facebook/rocksdb/wiki

docs.singlestore.com

docs.timescale.com

Developer

Event Store Limited

Facebook, Inc.

SingleStore Inc.

Simer Plaha

Timescale

Initial release

2012

2013

2018

2017

Current release

21.2, February 2021

8.11.4, April 2024

8.5, January 2024

2.15.0, May 2024

License

Commercial or Open Source

Open Source

BSD

commercial

free developer edition available

Open Source

GNU Affero GPL V3.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

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

Scala

Server operating systems

Linux
Windows

Linux

64 bit version required

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

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

C++ API
Java API

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

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

Supported programming languages

C
C++
Go
Java
Perl
Python
Ruby

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

Java
Kotlin
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

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

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

hash partitioning

none

yes, across time and space (hash partitioning) attributes

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

Source-replica replication with hot standby and reads on replicas

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

yes

ACID

Atomic execution of operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

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

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...
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Competitive advantages

SingleStore’s competitive advantages include: Easy and Simplified Architecture with...
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Typical application scenarios

Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
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Key customers

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

Customers in various industries worldwide including US and International Industry...
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Licensing and pricing models

F ree Tier and Enterprise Edition
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