DBMS > Citus vs. EDB Postgres vs. JaguarDB vs. ObjectBox vs. SQLite

System Properties Comparison Citus vs. EDB Postgres vs. JaguarDB vs. ObjectBox vs. SQLite

Editorial information provided by DB-Engines

Name

Description

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

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

Performant, highly scalable DBMS for AI and IoT applications

Extremely fast embedded database for small devices, IoT and Mobile

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

Key-value store
Vector DBMS

Object oriented DBMS

Relational DBMS

Secondary database models

Document store

Document store
Spatial DBMS

Time Series DBMS

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

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	1.90
Rank	#135	Overall
	#63	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

Technical documentation

docs.citusdata.com

www.enterprisedb.com/docs

www.jaguardb.com/support.html

docs.objectbox.io

www.sqlite.org/docs.html

Developer

EnterpriseDB

DataJaguar, Inc.

ObjectBox Limited

Dwayne Richard Hipp

Initial release

2010

2005

2015

2017

2000

Current release

8.1, December 2018

14, December 2021

3.3 July 2023

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

commercial

BSD for PostgreSQL-components

Open Source

GPL V3.0

Open Source

Apache License 2.0

Open Source

Public Domain

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.

Implementation language

C++

the server part. Clients available in other languages

C and C++

Server operating systems

Linux

Linux
Windows

Linux

Android
iOS
Linux
macOS
Windows

server-less

Data scheme

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

standard, with numerous extensions

yes

standard with numerous extensions

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

SQL-92 is not fully supported

APIs and other access methods

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

JDBC
ODBC

Proprietary native API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

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

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

user defined functions

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

user defined functions

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

by hash, list or range

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

Multi-source replication

online/offline synchronization between client and server

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

via file-system locks

Durability

Support for making data persistent

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 rights according to SQL-standard

rights management via user accounts

yes

More information provided by the system vendor

News

The first On-Device Vector Database: ObjectBox 4.0
16 May 2024

Edge AI: The era of on-device AI
23 April 2024

In-Memory Database Use Cases
15 February 2024

Data Viewer for Objects – announcing ObjectBox Admin
14 November 2023

Vector Databases for Edge AI
9 August 2023

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