DBMS > DolphinDB vs. Kinetica vs. PostGIS vs. RocksDB vs. SiriDB

System Properties Comparison DolphinDB vs. Kinetica vs. PostGIS vs. RocksDB vs. SiriDB

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.

Fully vectorized database across both GPUs and CPUs

Spatial extension of PostgreSQL

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Open Source Time Series DBMS

Primary database model

Time Series DBMS
Vector DBMS

Secondary database models

Relational DBMS

Spatial DBMS
Time Series DBMS

Relational DBMS

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

Score	2.72
Rank	#100	Overall
	#8	Time Series DBMS
	#5	Vector DBMS

Score	0.42
Rank	#261	Overall
	#120	Relational DBMS

Score	20.16
Rank	#29	Overall
	#1	Spatial DBMS

Score	2.84
Rank	#97	Overall
	#16	Key-value stores

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Website

Technical documentation

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

docs.kinetica.com

postgis.net/documentation

github.com/facebook/rocksdb/wiki

docs.siridb.com

Developer

DolphinDB, Inc

Kinetica

Facebook, Inc.

Cesbit

Initial release

2018

2012

2005

2013

2017

Current release

v2.00.4, January 2022

7.1, August 2021

3.4.2, February 2024

9.4.0, June 2024

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

GPL v2.0

Open Source

BSD

Open Source

MIT License

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++

C, C++

C++

Server operating systems

Linux
Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data

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

SQL-like DML and DDL statements

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
RESTful HTTP API

C++ API
Java API

HTTP API

Supported programming languages

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

C++
Java
JavaScript (Node.js)
Python

C
C++
Go
Java
Perl
Python
Ruby

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

yes

based on PostgreSQL

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

based on PostgreSQL

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

yes

Concurrency

Support for concurrent manipulation of data

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

GPU vRAM or System RAM

yes

User concepts

Access control

Administrators, Users, Groups

Access rights for users and roles on table level

yes

based on PostgreSQL

simple rights management via user accounts

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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