DBMS > IBM Db2 Event Store vs. Kinetica vs. Oracle Berkeley DB vs. RocksDB

System Properties Comparison IBM Db2 Event Store vs. Kinetica vs. Oracle Berkeley DB vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

Fully vectorized database across both GPUs and CPUs

Widely used in-process key-value store

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

Primary database model

Event Store
Time Series DBMS

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Key-value store

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

www.ibm.com/products/db2-event-store

www.kinetica.com

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

rocksdb.org

Technical documentation

www.ibm.com/docs/en/db2-event-store

docs.kinetica.com

docs.oracle.com/cd/E17076_05/html/index.html

github.com/facebook/rocksdb/wiki

Developer

IBM

Kinetica

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Facebook, Inc.

Initial release

2017

2012

1994

2013

Current release

2.0

7.1, August 2021

18.1.40, May 2020

9.2.1, May 2024

License

Commercial or Open Source

commercial

free developer edition available

commercial

Open Source

commercial license available

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

C, C++

C, Java, C++ (depending on the Berkeley DB edition)

C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux

Data scheme

yes

schema-free

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

SQL-like DML and DDL statements

yes

SQL interfaced based on SQLite is available

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

C++ API
Java API

Supported programming languages

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

C++
Java
JavaScript (Node.js)
Python

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual 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

ACID

yes

Concurrency

Support for concurrent manipulation of data

No - written data is immutable

yes

Durability

Support for making data persistent

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

GPU vRAM or System RAM

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

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