DBMS > Citus vs. GeoMesa vs. Sadas Engine vs. SingleStore vs. SiriDB

System Properties Comparison Citus vs. GeoMesa vs. Sadas Engine vs. SingleStore vs. SiriDB

Editorial information provided by DB-Engines

Name

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

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

Open Source Time Series DBMS

Primary database model

Secondary database models

Document store

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	5.60
Rank	#62	Overall
	#35	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

Technical documentation

docs.citusdata.com

www.geomesa.org/documentation/stable/user/index.html

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.singlestore.com

docs.siridb.com

Developer

CCRi and others

SADAS s.r.l.

SingleStore Inc.

Cesbit

Initial release

2010

2014

2006

2013

2017

Current release

8.1, December 2018

4.0.5, February 2024

8.0

8.5, January 2024

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

Open Source

Apache License 2.0

commercial

free trial version available

commercial

free developer edition available

Open Source

MIT License

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

Scala

C++

C++, Go

Server operating systems

Linux

AIX
Linux
Windows

Linux

64 bit version required

Linux

Data scheme

yes

Typing

predefined data types such as float or date

yes

Numeric data

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

specific XML type available, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

standard, with numerous extensions

yes

but no triggers and foreign keys

APIs and other access methods

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

JDBC
ODBC
Proprietary protocol

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

HTTP API

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C
C#
C++
Groovy
Java
PHP
Python

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

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

depending on storage layer

horizontal partitioning

Sharding

hash partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

depending on storage layer

none

Source-replica replication

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

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

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

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.

depending on storage layer

yes

managed by 'Learn by Usage'

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

depending on the DBMS used for storage

Access rights for users, groups and roles according to SQL-standard

Fine grained access control via users, groups and roles

simple rights management via user accounts

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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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
» 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

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