DBMS > FatDB vs. ObjectBox vs. Postgres-XL vs. Splice Machine

System Properties Comparison FatDB vs. ObjectBox vs. Postgres-XL vs. Splice Machine

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Document store
Key-value store

Object oriented DBMS
Vector DBMS

Relational DBMS

Secondary database models

Time Series DBMS

Document store
Spatial DBMS

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

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS
	#7	Vector DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

github.com/objectbox
objectbox.io

www.postgres-xl.org

splicemachine.com

Technical documentation

docs.objectbox.io

www.postgres-xl.org/documentation

splicemachine.com/how-it-works

Developer

FatCloud

ObjectBox Limited

Splice Machine

Initial release

2012

2017

2014

since 2012, originally named StormDB

2014

Current release

4.0 (May 2024)

10 R1, October 2018

3.1, March 2021

License

Commercial or Open Source

commercial

Bindings are released under Apache 2.0

Apache License 2.0

Open Source

Mozilla public license

Open Source

AGPL 3.0, commercial license available

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 and C++

Java

Server operating systems

Windows

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Linux
macOS

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, plus "flex" map-like types

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

Via inetgration in SQL Server

yes

distributed, parallel query execution

yes

APIs and other access methods

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

Proprietary native API

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

JDBC
Native Spark Datasource
ODBC

Supported programming languages

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

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

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes

via applications

user defined functions

yes

Java

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Data sync between devices allowing occasional connected databases to work completely offline

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Can implement custom security layer via applications

yes

fine grained access rights according to SQL-standard

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

More information provided by the system vendor

News

The on-device Vector Database for Android and Java
29 May 2024

Vector search: making sense of search queries
29 May 2024

Python on-device Vector and Object Database for Local AI
28 May 2024

Evolution of search: traditional vs vector search
23 May 2024

On-device Vector Database for Dart/Flutter
21 May 2024

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