DBMS > DolphinDB vs. MySQL vs. OpenQM vs. SAP SQL Anywhere vs. Sphinx

System Properties Comparison DolphinDB vs. MySQL vs. OpenQM vs. SAP SQL Anywhere vs. Sphinx

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.

Widely used open source RDBMS

QpenQM is a high-performance, self-tuning, multi-value DBMS

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Time Series DBMS
Vector DBMS

Relational DBMS

Key/Value like access via memcached API

Multivalue DBMS

Relational DBMS

Search engine

Secondary database models

Relational DBMS

Document store
Spatial 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	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Score	0.28
Rank	#291	Overall
	#10	Multivalue DBMS

Score	3.50
Rank	#81	Overall
	#44	Relational DBMS

Score	5.97
Rank	#56	Overall
	#5	Search engines

Website

www.dolphindb.com

www.mysql.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

www.sap.com/products/technology-platform/sql-anywhere.html

sphinxsearch.com

Technical documentation

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

dev.mysql.com/doc

help.sap.com/docs/SAP_SQL_Anywhere

sphinxsearch.com/docs

Developer

DolphinDB, Inc

Oracle

since 2010, originally MySQL AB, then Sun

Rocket Software, originally Martin Phillips

SAP

formerly Sybase

Sphinx Technologies Inc.

Initial release

2018

1995

1993

1992

2001

Current release

v2.00.4, January 2022

9.0.0, July 2024

3.4-12

17, July 2015

3.5.1, February 2023

License

Commercial or Open Source

commercial

free community version available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPLv2, extended commercial license available

commercial

Open Source

GPL version 2, commercial licence available

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 and C++

C++

Server operating systems

Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

with some exceptions

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

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

yes

SQL-like query language (SphinxQL)

APIs and other access methods

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

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
HTTP API
JDBC
ODBC

Proprietary protocol

Supported programming languages

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
Basic
C
Java
Objective C
PHP
Python

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

yes, in C/C++, Java, .Net or Perl

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

yes

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes

Source-replica replication

Database mirroring

none

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

not for MyISAM storage engine

yes

Transaction concepts

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

yes

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

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 with fine-grained authorization concept

no user groups or roles

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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