DBMS > DolphinDB vs. Ignite vs. Ingres vs. PostgreSQL

System Properties Comparison DolphinDB vs. Ignite vs. Ingres vs. PostgreSQL

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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.

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.

Well established RDBMS

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Primary database model

Time Series DBMS

Key-value store
Relational DBMS

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Secondary database models

Relational DBMS

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

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

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Website

www.dolphindb.com

ignite.apache.org

www.actian.com/databases/ingres

www.postgresql.org

Technical documentation

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

apacheignite.readme.io/docs

docs.actian.com/ingres

www.postgresql.org/docs

Developer

DolphinDB, Inc

Apache Software Foundation

Actian Corporation

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

2018

2015

1974

originally developed at University Berkely in early 1970s

1989

1989: Postgres, 1996: PostgreSQL

Current release

v2.00.4, January 2022

Apache Ignite 2.6

11.2, May 2022

16.3, May 2024

License

Commercial or Open Source

commercial

free community version available

Open Source

Apache 2.0

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C++, Java, .Net

Server operating systems

Linux
Windows

Linux
OS X
Solaris
Windows

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
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

but tools for importing/exporting data from/to XML-files available

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

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

yes

standard with numerous extensions

APIs and other access methods

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

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

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

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

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

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

yes

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

partitioning by range, list and (since PostgreSQL 11) by hash

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes (replicated cache)

Ingres Replicator

Source-replica replication

other methods possible by using 3rd party extensions

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

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

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

More information provided by the system vendor

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