DBMS > Badger vs. BigObject vs. HBase

System Properties Comparison Badger vs. BigObject vs. HBase

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Editorial information provided by DB-Engines

Name

Description

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

Analytic DBMS for real-time computations and queries

Wide-column store based on Apache Hadoop and on concepts of BigTable

Primary database model

Key-value store

Relational DBMS

a hierachical model (tree) can be imposed

Wide column store

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

Score	0.20
Rank	#325	Overall
	#49	Key-value stores

Score	0.13
Rank	#342	Overall
	#150	Relational DBMS

Score	31.25
Rank	#26	Overall
	#2	Wide column stores

Website

github.com/dgraph-io/badger

bigobject.io

hbase.apache.org

Technical documentation

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

docs.bigobject.io

hbase.apache.org/book.html

Developer

DGraph Labs

BigObject, Inc.

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Initial release

2017

2015

2008

Current release

2.3.4, January 2021

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free community edition available

Open Source

Apache version 2

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

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
Unix
Windows

using Cygwin

Data scheme

schema-free

yes

schema-free, schema definition possible

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

fluentd
ODBC
RESTful HTTP API

Java API
RESTful HTTP API
Thrift

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

Server-side scripts

Stored procedures

Lua

yes

Coprocessors in Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

Transaction concepts

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

Single row ACID (across millions of columns)

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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.

yes

User concepts

Access control

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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More resources

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