DBMS > IBM Db2 Event Store vs. Microsoft Azure Table Storage vs. RocksDB vs. Splunk vs. TerarkDB

System Properties Comparison IBM Db2 Event Store vs. Microsoft Azure Table Storage vs. RocksDB vs. Splunk vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

A Wide Column Store for rapid development using massive semi-structured datasets

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

Analytics Platform for Big Data

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Event Store
Time Series DBMS

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

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

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

Score	86.45
Rank	#14	Overall
	#2	Search engines

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

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

azure.microsoft.com/en-us/services/storage/tables

rocksdb.org

www.splunk.com

github.com/bytedance/terarkdb

Technical documentation

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

github.com/facebook/rocksdb/wiki

docs.splunk.com/Documentation/Splunk

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

IBM

Microsoft

Facebook, Inc.

Splunk Inc.

ByteDance, originally Terark

Initial release

2017

2012

2013

2003

2016

Current release

2.0

8.11.4, April 2024

License

Commercial or Open Source

commercial

free developer edition available

commercial

Open Source

BSD

commercial

Limited free edition and free developer edition available

commercial

restricted open source version available

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 and C++

C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

hosted

Linux

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

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

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

Splunk Search Processing Language for search commands

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

C++ API
Java API

HTTP REST

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

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

C
C++
Go
Java
Perl
Python
Ruby

C#
Java
JavaScript
PHP
Python
Ruby

C++
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

optimistic locking

yes

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights based on private key authentication or shared access signatures

Access rights for users and roles

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