DBMS > BoltDB vs. HBase vs. Microsoft Azure AI Search vs. Oracle Berkeley DB vs. RocksDB

System Properties Comparison BoltDB vs. HBase vs. Microsoft Azure AI Search vs. Oracle Berkeley DB vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

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

Search-as-a-service for web and mobile app development

Widely used in-process key-value store

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Key-value store

Secondary database models

Vector DBMS

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

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

github.com/boltdb/bolt

hbase.apache.org

azure.microsoft.com/en-us/services/search

www.oracle.com/database/technologies/related/berkeleydb.html

rocksdb.org

Technical documentation

hbase.apache.org/book.html

learn.microsoft.com/en-us/azure/search

docs.oracle.com/cd/E17076_05/html/index.html

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Microsoft

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Facebook, Inc.

Initial release

2013

2008

2015

1994

2013

Current release

2.3.4, January 2021

18.1.40, May 2020

9.2.1, May 2024

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache version 2

commercial

Open Source

commercial license available

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C, Java, C++ (depending on the Berkeley DB edition)

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
Unix
Windows

using Cygwin

hosted

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux

Data scheme

schema-free

schema-free, schema definition possible

yes

schema-free

Typing

predefined data types such as float or date

options to bring your own types, AVRO

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

APIs and other access methods

Java API
RESTful HTTP API
Thrift

RESTful HTTP API

C++ API
Java API

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

C#
Java
JavaScript
Python

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Coprocessors in Java

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

yes

Implicit feature of the cloud service

Source-replica replication

yes

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

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

Single row ACID (across millions of columns)

ACID

yes

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.

yes

User concepts

Access control

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

yes

using Azure authentication

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