DBMS > Apache Impala vs. ArangoDB vs. DataFS vs. Realm

System Properties Comparison Apache Impala vs. ArangoDB vs. DataFS vs. Realm

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Native multi-model DBMS for graph, document, key/value and search. All in one engine and accessible with one query language.

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Search engine

Object oriented DBMS

Document store

Secondary database models

Document store

Graph DBMS

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

Score	10.63
Rank	#40	Overall
	#24	Relational DBMS

Score	3.30
Rank	#82	Overall
	#14	Document stores
	#5	Graph DBMS
	#10	Key-value stores
	#10	Search engines

Score	0.02
Rank	#369	Overall
	#18	Object oriented DBMS

Score	7.18
Rank	#52	Overall
	#8	Document stores

Website

Technical documentation

impala.apache.org/impala-docs.html

docs.arangodb.com

dev.mobiland.com/Overview.xsp

realm.io/docs

Social network pages

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

ArangoDB Inc.

Mobiland AG

Realm, acquired by MongoDB in May 2019

Initial release

2013

2012

2018

2014

Current release

4.1.0, June 2022

3.11.5, November 2023

1.1.263, October 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2; Commercial license (Enterprise) available

commercial

Open Source

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.

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Implementation language

C++

Server operating systems

Linux

Linux
OS X
Windows

Windows

Android
Backend: server-less
iOS
Windows

Data scheme

yes

schema-free

automatically recognizes schema within a collection

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

Typing

predefined data types such as float or date

yes

string, double, boolean, list, hash

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

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

AQL
Foxx Framework
Graph API (Gremlin)
GraphQL query language
HTTP API
Java & SpringData
JSON style queries
VelocyPack/VelocyStream

.NET Client API
Proprietary client DLL
WinRT client

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
Clojure
Elixir
Go
Java
JavaScript (Node.js)
PHP
Python
R
Rust

.Net
C
C#
C++
VB.Net

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

JavaScript

runs within the applications so server-side scripts are unnecessary

Triggers

no, except callback-events from server when changes happened

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

since version 2.0

Proprietary Sharding system

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication with configurable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

can be done with stored procedures in JavaScript

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

configurable per collection or per write
Immediate Consistency
OneShard (highly available, fault-tolerant deployment mode with ACID semantics)

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

yes

Transaction concepts

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

ACID

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

based on Apache Sentry and Kerberos

yes

Windows-Profile

yes

More information provided by the system vendor

Specific characteristics

Graph and Beyond. With more than 11,000 stargazers on GitHub, ArangoDB is the leading...
» more

Competitive advantages

Consolidation: As a native multi-model database, can be used as a full blown document...
» more

Typical application scenarios

Native multi-model in ArangoDB is being used for a broad range of projects across...
» more

Key customers

Cisco, Barclays, Refinitive, Siemens Mentor, Kabbage, Liaison, Douglas, MakeMyTrip,...
» more

Market metrics

ArangoDB is the leading native multi-model database with over 11,000 stargazers on...
» more

Licensing and pricing models

Very permissive Apache 2 License for Community Edition & commercial licenses are...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

The Weight of Relational Databases: Time for Multi-Model?
29 August 2017, Luca Olivari (guest author)

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MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

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Recent citations in the news

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29 July 2021, iProgrammer

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

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30 May 2023, Datanami

Graph, machine learning, hype, and beyond: ArangoDB open source multi-model database releases version 3.7
27 August 2020, ZDNet

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23 June 2019, Business Insider

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22 August 2019, TechTarget

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12 September 2017, Solutions Review

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