DBMS > Bangdb vs. IBM Db2 Event Store vs. SAP SQL Anywhere vs. Splunk

System Properties Comparison Bangdb vs. IBM Db2 Event Store vs. SAP SQL Anywhere vs. Splunk

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Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

Distributed Event Store optimized for Internet of Things use cases

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Analytics Platform for Big Data

Primary database model

Document store
Graph DBMS
Time Series DBMS

Event Store
Time Series DBMS

Relational DBMS

Search engine

Secondary database models

Spatial DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

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

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

bangdb.com

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

www.sap.com/products/technology-platform/sql-anywhere.html

www.splunk.com

Technical documentation

docs.bangdb.com

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

help.sap.com/docs/SAP_SQL_Anywhere

docs.splunk.com/Documentation/Splunk

Developer

Sachin Sinha, BangDB

IBM

SAP

formerly Sybase

Splunk Inc.

Initial release

2012

2017

1992

2003

Current release

BangDB 2.0, October 2021

2.0

17, July 2015

License

Commercial or Open Source

Open Source

BSD 3

commercial

free developer edition available

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++

C and C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

through the embedded Spark runtime

yes

Splunk Search Processing Language for search commands

APIs and other access methods

Proprietary protocol
RESTful HTTP API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
HTTP API
JDBC
ODBC

HTTP REST

Supported programming languages

C
C#
C++
Java
Python

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

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

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

yes, in C/C++, Java, .Net or Perl

yes

Triggers

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

Active-active shard replication

Source-replica replication

Database mirroring

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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, optimistic concurrency control

No - written data is immutable

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

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, run db with in-memory only mode

yes

User concepts

Access control

yes (enterprise version only)

fine grained access rights according to SQL-standard

Access rights for users and roles

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