DBMS > Apache Impala vs. BoltDB vs. Firebase Realtime Database vs. Riak KV vs. RocksDB

System Properties Comparison Apache Impala vs. BoltDB vs. Firebase Realtime Database vs. Riak KV vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Distributed, fault tolerant key-value store

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

Primary database model

with links between data sets and object tags for the creation of secondary indexes

Key-value store

Secondary database models

Document store

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

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

Website

impala.apache.org

github.com/boltdb/bolt

firebase.google.com/products/realtime-database

rocksdb.org

Technical documentation

impala.apache.org/impala-docs.html

firebase.google.com/docs/database

www.tiot.jp/riak-docs/riak/kv/latest

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Google

acquired by Google 2014

OpenSource, formerly Basho Technologies

Facebook, Inc.

Initial release

2013

2012

2009

2013

Current release

4.1.0, June 2022

3.2.0, December 2022

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

MIT License

commercial

Open Source

Apache version 2, commercial enterprise edition

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Erlang

C++

Server operating systems

Linux

BSD
Linux
OS X
Solaris
Windows

hosted

Linux
OS X

Linux

Data scheme

yes

schema-free

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

restricted

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

Android
iOS
JavaScript API
RESTful HTTP API

HTTP API
Native Erlang Interface

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC

Java
JavaScript
Objective-C

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

limited functionality with using 'rules'

Erlang

Triggers

Callbacks are triggered when data changes

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

no "single point of failure"

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency

Foreign keys

Referential integrity

links between data sets can be stored

Transaction concepts

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

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 rights for users, groups and roles

based on Apache Sentry and Kerberos

yes, based on authentication and database rules

yes, using Riak Security

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.