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

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

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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.

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

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

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

Object oriented DBMS
Vector DBMS

Secondary database models

Spatial DBMS

Time Series DBMS

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

Score	2.85
Rank	#96	Overall
	#50	Relational DBMS
	#6	Time Series DBMS

Score	7.57
Rank	#47	Overall
	#30	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

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

Website

druid.apache.org

www.h2database.com

nsdb.io

github.com/objectbox
objectbox.io

Technical documentation

druid.apache.org/docs/latest/design

www.h2database.com/html/main.html

nsdb.io/Architecture

docs.objectbox.io

Developer

Apache Software Foundation and contributors

Thomas Mueller

ObjectBox Limited

Initial release

2012

2005

2017

Current release

30.0.0, June 2024

2.2.220, July 2023

4.0 (May 2024)

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

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

Open Source

Apache Version 2.0

Bindings are released under Apache 2.0

Apache License 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Java, Scala

C and C++

Server operating systems

Linux
OS X
Unix

All OS with a Java VM

Linux
macOS

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Data scheme

yes

schema-less columns are supported

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

yes, plus "flex" map-like 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.

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL for querying

yes

SQL-like query language

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
ODBC

gRPC
HTTP REST
WebSocket

Proprietary native API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Java

Java
Scala

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

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Sharding

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

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

Durability

Support for making data persistent

yes

Using Apache Lucene

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

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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More resources

Recent citations in the news

Imply Announces the Availability of Imply Polaris, a Database-as-a-Service Built from Apache Druid, on Microsoft Azure
26 June 2024, Yahoo Finance

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

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

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

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

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