DBMS > Badger vs. EventStoreDB vs. Trafodion

System Properties Comparison Badger vs. EventStoreDB vs. Trafodion

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

Transactional SQL-on-Hadoop DBMS

Primary database model

Key-value store

Event Store

Relational DBMS

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Website

github.com/dgraph-io/badger

www.eventstore.com

trafodion.apache.org

Technical documentation

godoc.org/github.com/dgraph-io/badger

developers.eventstore.com

trafodion.apache.org/documentation.html

Developer

DGraph Labs

Event Store Limited

Apache Software Foundation, originally developed by HP

Initial release

2017

2012

2014

Current release

21.2, February 2021

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++, Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
Windows

Linux

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

User concepts

Access control

fine grained access rights according to SQL-standard

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