DBMS > IBM Db2 warehouse vs. RocksDB vs. Sequoiadb

System Properties Comparison IBM Db2 warehouse vs. RocksDB vs. Sequoiadb

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Editorial information provided by DB-Engines

Name

Description

Cloud-based data warehousing service

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

NewSQL database with distributed OLTP and SQL

Primary database model

Relational DBMS

Key-value store

Document store
Relational DBMS

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

Score	1.30
Rank	#164	Overall
	#75	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

www.ibm.com/products/db2/warehouse

rocksdb.org

www.sequoiadb.com

Technical documentation

github.com/facebook/rocksdb/wiki

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

IBM

Facebook, Inc.

Sequoiadb Ltd.

Initial release

2014

2013

Current release

8.11.4, April 2024

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

Server: AGPL; Client: Apache V2

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++

Server operating systems

hosted

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

.NET Client API
JDBC
ODBC
OLE DB

C++ API
Java API

proprietary protocol using JSON

Supported programming languages

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

C
C++
Go
Java
Perl
Python
Ruby

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

PL/SQL, SQL PL

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

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

fine grained access rights according to SQL-standard

simple password-based access control

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