DBMS > DolphinDB vs. H2 vs. InfinityDB vs. Riak KV

System Properties Comparison DolphinDB vs. H2 vs. InfinityDB vs. Riak KV

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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.

A Java embedded Key-Value Store which extends the Java Map interface

Distributed, fault tolerant key-value store

Primary database model

Time Series DBMS

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Secondary database models

Relational DBMS

Spatial DBMS

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

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Website

www.dolphindb.com

www.h2database.com

boilerbay.com

Technical documentation

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

www.h2database.com/html/main.html

boilerbay.com/infinitydb/manual

www.tiot.jp/riak-docs/riak/kv/latest

Developer

DolphinDB, Inc

Thomas Mueller

Boiler Bay Inc.

OpenSource, formerly Basho Technologies

Initial release

2018

2005

2002

2009

Current release

v2.00.4, January 2022

2.2.220, July 2023

4.0

3.2.0, December 2022

License

Commercial or Open Source

commercial

free community version available

Open Source

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

commercial

Open Source

Apache version 2, commercial enterprise edition

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Erlang

Server operating systems

Linux
Windows

All OS with a Java VM

Linux
OS X

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

restricted

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

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

JDBC
ODBC

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

HTTP API
Native Erlang Interface

Supported programming languages

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

Java

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

Java Stored Procedures and User-Defined Functions

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

no "single point of failure"

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

none

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Eventual Consistency

Foreign keys

Referential integrity

yes

manual creation possible, using inversions based on multi-value capability

links between data sets can be stored

Transaction concepts

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

yes

ACID

Optimistic locking for transactions; no isolation for bulk loads

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

yes, using Riak Security

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