DBMS > Datomic vs. DolphinDB vs. EventStoreDB vs. Linter

System Properties Comparison Datomic vs. DolphinDB vs. EventStoreDB vs. Linter

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Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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.

Industrial-strength, open-source database solution built from the ground up for event sourcing.

RDBMS for high security requirements

Primary database model

Secondary database models

Relational DBMS

Spatial DBMS

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	1.19
Rank	#173	Overall
	#1	Event Stores

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Website

Technical documentation

docs.datomic.com

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

developers.eventstore.com

Developer

Cognitect

DolphinDB, Inc

Event Store Limited

relex.ru

Initial release

2012

2018

2012

1990

Current release

1.0.6735, June 2023

v2.00.4, January 2022

21.2, February 2021

License

Commercial or Open Source

commercial

limited edition free

commercial

free community version available

Open Source

commercial

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

Java, Clojure

C++

C and C++

Server operating systems

All OS with a Java VM

Linux
Windows

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

RESTful HTTP API

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

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Supported programming languages

Clojure
Java

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

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

yes

User concepts

Access control

Administrators, Users, Groups

fine grained access rights according to SQL-standard

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