DBMS > DolphinDB vs. IBM Db2 vs. MySQL vs. Rockset vs. Sqrrl

System Properties Comparison DolphinDB vs. IBM Db2 vs. MySQL vs. Rockset vs. Sqrrl

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been 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.

Common in IBM host environments, 2 different versions for host and Windows/Linux

Widely used open source RDBMS

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Time Series DBMS

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Relational DBMS

Key/Value like access via memcached API

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Relational DBMS

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Document store
Spatial DBMS

Relational DBMS
Search engine

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Website

www.dolphindb.com

www.ibm.com/products/db2

www.mysql.com

rockset.com

sqrrl.com

Technical documentation

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

www.ibm.com/docs/en/db2

dev.mysql.com/doc

docs.rockset.com

Developer

DolphinDB, Inc

IBM

Oracle

since 2010, originally MySQL AB, then Sun

Rockset

Amazon

originally Sqrrl Data, Inc.

Initial release

2018

1983

host version

1995

2019

2012

Current release

v2.00.4, January 2022

12.1, October 2016

8.4.0, April 2024

License

Commercial or Open Source

commercial

free community version available

commercial

free version is available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C and C++

C++

Java

Server operating systems

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows
z/OS

FreeBSD
Linux
OS X
Solaris
Windows

hosted

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

dynamic typing

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

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

Read-only SQL queries, including JOINs

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
JSON style queries

MongoDB compatible
ODBC
XQuery

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP REST

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

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

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

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

Go
Java
JavaScript (Node.js)
Python

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

only with Windows/Unix/Linux Version

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Automatic sharding

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

yes

with separate tools (MQ, InfoSphere)

Multi-source replication
Source-replica replication

yes

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

yes

ACID

not for MyISAM storage engine

Atomic updates per row, document, or graph entity

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

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

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and organizations can be defined via Rockset console

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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