DBMS > Bangdb vs. EventStoreDB vs. Graphite vs. Transbase

System Properties Comparison Bangdb vs. EventStoreDB vs. Graphite vs. Transbase

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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

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Document store
Graph DBMS
Time Series DBMS

Event Store

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	1.19
Rank	#173	Overall
	#1	Event Stores

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

bangdb.com

www.eventstore.com

github.com/graphite-project/graphite-web

www.transaction.de/en/products/transbase.html

Technical documentation

docs.bangdb.com

developers.eventstore.com

graphite.readthedocs.io

www.transaction.de/en/products/transbase/features.html

Developer

Sachin Sinha, BangDB

Event Store Limited

Chris Davis

Transaction Software GmbH

Initial release

2012

2006

1987

Current release

BangDB 2.0, October 2021

21.2, February 2021

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache 2.0

commercial

free development license

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++

Python

C and C++

Server operating systems

Linux

Linux
Windows

Linux
Unix

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

Numeric data only

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.

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

HTTP API
Sockets

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
C#
C++
Java
Python

JavaScript (Node.js)
Python

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

none

Immediate Consistency

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

yes, optimistic concurrency control

yes

locking

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

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

User concepts

Access control

yes (enterprise version only)

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

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1 June 2015, Paul Andlinger

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Recent citations in the news

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