DBMS > DolphinDB vs. Graph Engine vs. IBM Db2 warehouse vs. InterSystems Caché

System Properties Comparison DolphinDB vs. Graph Engine vs. IBM Db2 warehouse vs. InterSystems Caché

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Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

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 distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Cloud-based data warehousing service

A multi-model DBMS and application server

Primary database model

Time Series DBMS

Graph DBMS
Key-value store

Relational DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Secondary database models

Relational DBMS

Document store

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	1.30
Rank	#164	Overall
	#75	Relational DBMS

Website

www.dolphindb.com

www.graphengine.io

www.ibm.com/products/db2/warehouse

www.intersystems.com/products/cache

Technical documentation

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

www.graphengine.io/docs/manual

docs.intersystems.com

Developer

DolphinDB, Inc

Microsoft

IBM

InterSystems

Initial release

2018

2010

2014

1997

Current release

v2.00.4, January 2022

2018.1.4, May 2020

License

Commercial or Open Source

commercial

free community version available

Open Source

MIT License

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

.NET and C

Server operating systems

Linux
Windows

.NET

hosted

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

yes

depending on used data model

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.

Import/export of XML data possible

yes

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

RESTful HTTP API

.NET Client API
JDBC
ODBC
OLE DB

.NET Client API
JDBC
ODBC
RESTful HTTP API

Supported programming languages

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

C#
C++
F#
Visual Basic

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C#
C++
Java

Server-side scripts

Stored procedures

yes

PL/SQL, SQL PL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

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