DBMS > H2 vs. ObjectBox vs. TimescaleDB vs. YottaDB

System Properties Comparison H2 vs. ObjectBox vs. TimescaleDB vs. YottaDB

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Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

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

A fast and solid embedded Key-value store

Primary database model

Relational DBMS

Object oriented DBMS
Vector DBMS

Time Series DBMS

Key-value store

Secondary database models

Spatial DBMS

Time Series DBMS

Relational DBMS

using the Octo plugin

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

Score	7.57
Rank	#47	Overall
	#30	Relational DBMS

Score	1.08
Rank	#179	Overall
	#6	Object oriented DBMS
	#9	Vector DBMS

Score	4.06
Rank	#73	Overall
	#5	Time Series DBMS

Score	0.21
Rank	#309	Overall
	#43	Key-value stores

Website

www.h2database.com

github.com/objectbox
objectbox.io

www.timescale.com

yottadb.com

Technical documentation

www.h2database.com/html/main.html

docs.objectbox.io

docs.timescale.com

yottadb.com/resources/documentation

Developer

Thomas Mueller

ObjectBox Limited

Timescale

YottaDB, LLC

Initial release

2005

2017

2001

Current release

2.2.220, July 2023

4.0 (May 2024)

2.15.0, May 2024

License

Commercial or Open Source

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Bindings are released under Apache 2.0

Apache License 2.0

Open Source

Apache 2.0

Open Source

AGPL 3.0

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.

Implementation language

Java

C and C++

Server operating systems

All OS with a Java VM

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Linux
OS X
Windows

Docker
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, plus "flex" map-like types

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

full PostgreSQL SQL syntax

by using the Octo plugin

APIs and other access methods

JDBC
ODBC

Proprietary native API

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

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

Java

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

Java Stored Procedures and 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

Partitioning methods

Methods for storing different data on different nodes

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

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

Source-replica replication with hot standby and reads on replicas

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

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

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

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

yes

fine grained access rights according to SQL-standard

Users and groups based on OS-security mechanisms

More information provided by the system vendor

News

MongoDB Realm & Device Sync alternatives – ObjectBox
17 September 2024

Local AI – what it is and why we need it
11 September 2024

First on-device Vector Database (aka Semantic Index) for iOS
24 July 2024

Retrieval Augmented Generation (RAG) with vector databases: Expanding AI Capabilities
18 June 2024

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

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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

Recent citations in the news

General availability: Latest version of the TimeScaleDB extension on Azure Database for PostgreSQL - Flexible Server
8 May 2024, azure.microsoft.com

Timescale Acquires PopSQL to Bring a Modern, Collaborative SQL GUI to PostgreSQL Developers
4 April 2024, PR Newswire

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

PostgreSQL is Now Faster than Pinecone, 75% Cheaper, with New Open Source Extensions
11 June 2024, PR Newswire

TimescaleDB goes distributed; implements ‘Chunking’ over ‘Sharding’ for scaling-out
22 August 2019, Packt Hub

provided by Google News

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