DBMS > Apache Impala vs. BoltDB vs. IBM Db2 Event Store vs. RocksDB vs. Splunk

System Properties Comparison Apache Impala vs. BoltDB vs. IBM Db2 Event Store vs. RocksDB vs. Splunk

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

An embedded key-value store for Go.

Distributed Event Store optimized for Internet of Things use cases

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

Analytics Platform for Big Data

Primary database model

Relational DBMS

Key-value store

Event Store
Time Series DBMS

Key-value store

Search engine

Secondary database models

Document store

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

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

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

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

impala.apache.org

github.com/boltdb/bolt

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

rocksdb.org

www.splunk.com

Technical documentation

impala.apache.org/impala-docs.html

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

github.com/facebook/rocksdb/wiki

docs.splunk.com/Documentation/Splunk

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

IBM

Facebook, Inc.

Splunk Inc.

Initial release

2013

2017

2013

2003

Current release

4.1.0, June 2022

2.0

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

MIT License

commercial

free developer edition available

Open Source

BSD

commercial

Limited free edition and free developer edition 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

BSD
Linux
OS X
Solaris
Windows

Linux

Linux, macOS, Windows for the developer addition

Linux

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

schema-free

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

SQL

Support of SQL

SQL-like DML and DDL statements

yes

through the embedded Spark runtime

Splunk Search Processing Language for search commands

APIs and other access methods

JDBC
ODBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

C++ API
Java API

HTTP REST

Supported programming languages

All languages supporting JDBC/ODBC

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

C
C++
Go
Java
Perl
Python
Ruby

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Active-active shard replication

yes

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

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

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

Access rights for users and roles

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