DBMS > Apache Impala vs. Badger vs. DataFS vs. Datomic

System Properties Comparison Apache Impala vs. Badger vs. DataFS vs. Datomic

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Primary database model

Secondary database models

Document store

Graph DBMS

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

Score	10.63
Rank	#40	Overall
	#24	Relational DBMS

Score	0.14
Rank	#328	Overall
	#48	Key-value stores

Score	0.02
Rank	#369	Overall
	#18	Object oriented DBMS

Score	1.55
Rank	#144	Overall
	#67	Relational DBMS

Website

impala.apache.org

github.com/dgraph-io/badger

newdatabase.com

www.datomic.com

Technical documentation

impala.apache.org/impala-docs.html

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

dev.mobiland.com/Overview.xsp

docs.datomic.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

DGraph Labs

Mobiland AG

Cognitect

Initial release

2013

2017

2018

2012

Current release

4.1.0, June 2022

1.1.263, October 2022

1.0.7180, July 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

commercial

limited edition free

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++

Java, Clojure

Server operating systems

Linux

BSD
Linux
OS X
Solaris
Windows

Windows

All OS with a Java VM

Data scheme

yes

schema-free

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

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

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

.NET Client API
Proprietary client DLL
WinRT client

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C#
C++
VB.Net

Clojure
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Transaction Functions

Triggers

no, except callback-events from server when changes happened

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Proprietary Sharding system

none

But extensive use of caching in the application peers

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

But extensive use of caching in the application peers

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

In-memory capabilities

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

yes

recommended only for testing and development

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Windows-Profile

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More resources

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