DBMS > DolphinDB vs. H2 vs. Ignite

System Properties Comparison DolphinDB vs. H2 vs. Ignite

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Editorial information provided by DB-Engines

Name

Description

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

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

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Primary database model

Time Series DBMS

Relational DBMS

Key-value store
Relational DBMS

Secondary database models

Relational DBMS

Spatial DBMS

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Website

www.dolphindb.com

www.h2database.com

ignite.apache.org

Technical documentation

docs.dolphindb.cn/en/help200/index.html

www.h2database.com/html/main.html

apacheignite.readme.io/docs

Developer

DolphinDB, Inc

Thomas Mueller

Apache Software Foundation

Initial release

2018

2005

2015

Current release

v2.00.4, January 2022

2.2.220, July 2023

Apache Ignite 2.6

License

Commercial or Open Source

commercial

free community version available

Open Source

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

Open Source

Apache 2.0

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

C++

Java

C++, Java, .Net

Server operating systems

Linux
Windows

All OS with a Java VM

Linux
OS X
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

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-like query language

yes

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

JDBC
ODBC

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

Java

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

Java Stored Procedures and User-Defined Functions

yes (compute grid and cache interceptors can be used instead)

Triggers

yes

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

yes (replicated cache)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

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

yes

ACID

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

Administrators, Users, Groups

fine grained access rights according to SQL-standard

Security Hooks for custom implementations

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More resources

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