DBMS > Apache Impala vs. ArangoDB vs. JaguarDB vs. SQLite

System Properties Comparison Apache Impala vs. ArangoDB vs. JaguarDB vs. SQLite

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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.

Performant, highly scalable DBMS for AI and IoT applications

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Search engine

Key-value store
Vector DBMS

Relational DBMS

Secondary database models

Document store

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	0.00
Rank	#385	Overall
	#61	Key-value stores
	#16	Vector DBMS

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Website

Technical documentation

impala.apache.org/impala-docs.html

docs.arangodb.com

www.jaguardb.com/support.html

www.sqlite.org/docs.html

Social network pages

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

ArangoDB Inc.

DataJaguar, Inc.

Dwayne Richard Hipp

Initial release

2013

2012

2015

2000

Current release

4.1.0, June 2022

3.11.5, November 2023

3.3 July 2023

3.46.1 (13 August 2024), August 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2; Commercial license (Enterprise) available

Open Source

GPL V3.0

Open Source

Public Domain

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++

the server part. Clients available in other languages

Server operating systems

Linux

Linux
OS X
Windows

Linux

server-less

Data scheme

yes

schema-free

automatically recognizes schema within a collection

yes

dynamic column types

Typing

predefined data types such as float or date

yes

string, double, boolean, list, hash

yes

not rigid because of 'dynamic typing' concept.

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

SQL-92 is not fully supported

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

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

All languages supporting JDBC/ODBC

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

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

since version 2.0

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication with configurable replication factor

Multi-source replication

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)

Eventual 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

via file-system locks

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

rights management via user accounts

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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