DBMS > BoltDB vs. HBase vs. ObjectBox vs. Prometheus vs. RocksDB

System Properties Comparison BoltDB vs. HBase vs. ObjectBox vs. Prometheus 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

Extremely fast embedded database for small devices, IoT and Mobile

Open-source Time Series DBMS and monitoring system

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

Primary database model

Secondary database models

Time Series 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	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

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

Website

github.com/boltdb/bolt

Technical documentation

hbase.apache.org/book.html

docs.objectbox.io

prometheus.io/docs

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

ObjectBox Limited

Facebook, Inc.

Initial release

2013

2008

2017

2015

2013

Current release

2.3.4, January 2021

8.11.4, April 2024

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache version 2

Open Source

Apache License 2.0

Open Source

Apache 2.0

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
Unix
Windows

using Cygwin

Android
iOS
Linux
macOS
Windows

Linux
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

Numeric data only

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.

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

APIs and other access methods

Java API
RESTful HTTP API
Thrift

Proprietary native API

RESTful HTTP/JSON API

C++ API
Java API

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Coprocessors in Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

online/offline synchronization between client and server

yes

by Federation

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

none

Foreign keys

Referential integrity

yes

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

More information provided by the system vendor

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