DBMS > DolphinDB vs. H2GIS vs. Heroic vs. TerarkDB

System Properties Comparison DolphinDB vs. H2GIS vs. Heroic vs. TerarkDB

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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.

Spatial extension of H2

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Secondary database models

Relational DBMS

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

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

www.dolphindb.com

www.h2gis.org

github.com/spotify/heroic

github.com/bytedance/terarkdb

Technical documentation

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

www.h2gis.org/docs/home

spotify.github.io/heroic

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

DolphinDB, Inc

CNRS

Spotify

ByteDance, originally Terark

Initial release

2018

2013

2014

2016

Current release

v2.00.4, January 2022

License

Commercial or Open Source

commercial

free community version available

Open Source

LGPL 3.0

Open Source

Apache 2.0

commercial

restricted open source version available

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++

Server operating systems

Linux
Windows

Data scheme

yes

schema-free

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.

Secondary indexes

yes

via Elasticsearch

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

HQL (Heroic Query Language, a JSON-based language)
HTTP API

C++ API
Java API

Supported programming languages

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

Java

C++
Java

Server-side scripts

Stored procedures

yes

based on H2

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

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

yes

based on H2

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