DBMS > Hive vs. RavenDB vs. Realm vs. Riak KV vs. Transbase

System Properties Comparison Hive vs. RavenDB vs. Realm vs. Riak KV vs. Transbase

Editorial information provided by DB-Engines

Name

Description

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Open Source Operational and Transactional Enterprise NoSQL Document Database

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Distributed, fault tolerant key-value store

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Relational DBMS

Document store

Key-value store

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

Relational DBMS

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	7.60
Rank	#52	Overall
	#9	Document stores

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

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

hive.apache.org

ravendb.net

realm.io

www.transaction.de/en/products/transbase.html

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

ravendb.net/docs

realm.io/docs

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

www.transaction.de/en/products/transbase/features.html

Developer

Apache Software Foundation

initially developed by Facebook

Hibernating Rhinos

Realm, acquired by MongoDB in May 2019

OpenSource, formerly Basho Technologies

Transaction Software GmbH

Initial release

2012

2010

2014

2009

1987

Current release

3.1.3, April 2022

5.4, July 2022

3.2.0, December 2022

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

AGPL version 3, commercial license available

Open Source

Apache version 2, commercial enterprise edition

commercial

free development license

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

Erlang

C and C++

Server operating systems

All OS with a Java VM

Linux
macOS
Raspberry Pi
Windows

Android
Backend: server-less
iOS
Windows

Linux
OS X

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

yes

schema-free

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

restricted

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language (RQL)

yes

APIs and other access methods

JDBC
ODBC
Thrift

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

HTTP API
Native Erlang Interface

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C++
Java
PHP
Python

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
Java

with Android only
Objective-C
React Native
Swift

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#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

runs within the applications so server-side scripts are unnecessary

Erlang

yes

Triggers

yes

Change Listeners

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

none

selectable replication factor

Source-replica replication

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

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between data sets can be stored

yes

Transaction concepts

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

ACID, Cluster-wide transaction available

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

In-Memory realm

User concepts

Access control

Access rights for users, groups and roles

Authorization levels configured per client per database

yes

yes, using Riak Security

fine grained access rights according to SQL-standard

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