DBMS > Apache Druid vs. H2 vs. ObjectBox vs. searchxml

System Properties Comparison Apache Druid vs. H2 vs. ObjectBox vs. searchxml

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Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Object oriented DBMS
Vector DBMS

Native XML DBMS
Search engine

Secondary database models

Spatial DBMS

Time Series DBMS

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

Score	2.79
Rank	#97	Overall
	#50	Relational DBMS
	#7	Time Series DBMS

Score	7.32
Rank	#49	Overall
	#31	Relational DBMS

Score	1.10
Rank	#175	Overall
	#6	Object oriented DBMS
	#10	Vector DBMS

Score	0.00
Rank	#388	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

druid.apache.org

www.h2database.com

github.com/objectbox
objectbox.io

www.searchxml.net/category/products

Technical documentation

druid.apache.org/docs/latest/design

www.h2database.com/html/main.html

docs.objectbox.io

www.searchxml.net/support/handouts

Developer

Apache Software Foundation and contributors

Thomas Mueller

ObjectBox Limited

informationpartners gmbh

Initial release

2012

2005

2017

2015

Current release

30.0.0, June 2024

2.2.220, July 2023

4.0 (May 2024)

1.0

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

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

Bindings are released under Apache 2.0

Apache License 2.0

commercial

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++

C++

Server operating systems

Linux
OS X
Unix

All OS with a Java VM

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Windows

Data scheme

yes

schema-less columns are supported

yes

schema-free

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

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
ODBC

Proprietary native API

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Java

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

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes

on the application server

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

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

yes

sychronisation to multiple collections

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

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

yes

Domain, group and role-based access control at the document level and for application services

More information provided by the system vendor

News

Bi-directional Offline-First Data Sync with MongoDB and ObjectBox
21 October 2024

The rise of small language models
2 October 2024

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

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More resources

Recent citations in the news

Apache® Druid Wins Best Big Data Product in the 2023 BigDATAwire Readers’ Choice Awards
26 January 2024, Business Wire

New DDoS malware Attacking Apache big-data stack, Hadoop, & Druid Servers
26 February 2024, GBHackers

'Lucifer' Botnet Turns Up the Heat on Apache Hadoop Servers
21 February 2024, Dark Reading

Apache Druid Takes Its Place In The Pantheon Of Databases
16 June 2022, The Next Platform

How to connect DataGrip to Apache Druid
18 October 2021, Towards Data Science

provided by Google News

Industrial IoT (IIoT) edge solution for railway operators – a Kapsch ObjectBox Case Study
21 June 2019, 1E9

provided by Google News

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