DBMS > DolphinDB vs. gStore vs. TimesTen

System Properties Comparison DolphinDB vs. gStore vs. TimesTen

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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.

A native Graph DBMS to store and maintain very large RDF datasets.

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Primary database model

Time Series DBMS
Vector DBMS

Graph DBMS
RDF store

Relational DBMS

Secondary database models

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	0.03
Rank	#367	Overall
	#37	Graph DBMS
	#18	RDF stores

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

www.dolphindb.com

en.gstore.cn

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

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

en.gstore.cn/#/enDocs

docs.oracle.com/en/database/other-databases/timesten/index.html

Developer

DolphinDB, Inc

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2018

2016

1998

Current release

v2.00.4, January 2022

1.2, November 2023

Release 22.1

License

Commercial or Open Source

commercial

free community version available

Open Source

BSD

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

C++

Server operating systems

Linux
Windows

Linux

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Data scheme

yes

schema-free and OWL/RDFS-schema support

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

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

HTTP API
SPARQL 1.1

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

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

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

C
C++
Java
Node.js
PL/SQL
Python

Server-side scripts

Stored procedures

yes

PL/SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
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

Immediate Consistency or Eventual Consistency depending on configuration

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

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

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

Users, roles and permissions, Role-Based Access Control (RBAC) supported

fine grained access rights according to SQL-standard

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