DBMS > Apache Impala vs. Fauna vs. RDF4J vs. YottaDB

System Properties Comparison Apache Impala vs. Fauna vs. RDF4J vs. YottaDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

A fast and solid embedded Key-value store

Primary database model

Relational DBMS

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

RDF store

Key-value store

Secondary database models

Document store

Relational DBMS

using the Octo plugin

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	1.52
Rank	#153	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.20
Rank	#317	Overall
	#47	Key-value stores

Website

Technical documentation

impala.apache.org/impala-docs.html

docs.fauna.com

rdf4j.org/documentation

yottadb.com/resources/documentation

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Fauna, Inc.

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

YottaDB, LLC

Initial release

2013

2014

2004

2001

Current release

4.1.0, June 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

AGPL 3.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Scala

Java

Server operating systems

Linux

hosted

Linux
OS X
Unix
Windows

Docker
Linux

Data scheme

yes

schema-free

yes

RDF Schemas

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

SQL

Support of SQL

SQL-like DML and DDL statements

by using the Octo plugin

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

All languages supporting JDBC/ODBC

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

Java
PHP
Python

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

Identity management, authentication, and access control

Users and groups based on OS-security mechanisms

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More resources

Recent citations in the news

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

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

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

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

provided by Google News

GraphDB Goes Open Source
27 January 2020, iProgrammer

Ontotext's GraphDB 8.10 Makes Knowledge Graph Experience Faster and Richer
13 June 2019, Markets Insider

provided by Google News

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