DBMS > Apache Impala vs. ArangoDB vs. IRONdb

System Properties Comparison Apache Impala vs. ArangoDB vs. IRONdb

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Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

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.

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Search engine

Time Series DBMS

Secondary database models

Document store

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

Score	11.68
Rank	#41	Overall
	#25	Relational DBMS

Score	2.85
Rank	#88	Overall
	#14	Document stores
	#4	Graph DBMS
	#13	Key-value stores
	#9	Search engines

Website

impala.apache.org

arangodb.com

www.circonus.com/solutions/time-series-database/

Technical documentation

impala.apache.org/impala-docs.html

docs.arangodb.com

docs.circonus.com/irondb/category/getting-started

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

ArangoDB Inc.

Circonus LLC.

Initial release

2013

2012

2017

Current release

4.1.0, June 2022

3.11.5, November 2023

V0.10.20, January 2018

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2; Commercial license (Enterprise) available

commercial

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

C++

C and C++

Server operating systems

Linux

Linux
OS X
Windows

Linux

Data scheme

yes

schema-free

automatically recognizes schema within a collection

schema-free

Typing

predefined data types such as float or date

yes

string, double, boolean, list, hash

yes

text, numeric, histograms

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

SQL-like query language (Circonus Analytics Query Language: CAQL)

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

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

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

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

JavaScript

yes, in Lua

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

since version 2.0

Automatic, metric affinity per node

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication with configurable replication factor

configurable replication factor, datacenter aware

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 per node, eventual consistency across nodes

Foreign keys

Referential integrity

yes

relationships in graphs

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.

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

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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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Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SD Times

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

Apache Doris just ‘graduated’: Why care about this SQL data warehouse
24 June 2022, InfoWorld

Apache Doris Analytical Database Graduates from Apache Incubator
20 June 2022, datanami.com

Apache Iceberg is now available on the Cloudera Data Platform
4 July 2022, techzine.eu

provided by Google News

ArangoDB raises $10 million for NoSQL database management
14 March 2019, VentureBeat

Top Open Source Graph Databases
3 June 2024, MarkTechPost

ArangoDB Boosts Performance and Usability Across Search, Graph, and Analytics with Release of ArangoDB 3.11
30 May 2023, PRWeb

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

ArangoDB advances graph database fortunes with new funding
6 October 2021, TechTarget

provided by Google News

Apica gets $6 million in funding and buys Circonus -
21 February 2024, Enterprise Times

provided by Google News

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