DBMS > Apache Impala vs. EsgynDB vs. KairosDB vs. OushuDB vs. RDF4J

System Properties Comparison Apache Impala vs. EsgynDB vs. KairosDB vs. OushuDB vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Distributed Time Series DBMS based on Cassandra or H2

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

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

Primary database model

Secondary database models

Document store

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	0.10
Rank	#355	Overall
	#154	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

impala.apache.org

www.esgyn.cn

github.com/kairosdb/kairosdb

www.oushu.com/product/oushuDB

rdf4j.org

Technical documentation

impala.apache.org/impala-docs.html

kairosdb.github.io

www.oushu.com/documentation

rdf4j.org/documentation

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Esgyn

Oushu

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

Initial release

2013

2015

2013

2004

Current release

4.1.0, June 2022

1.2.2, November 2018

4.0.1, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

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++, Java

Java

Server operating systems

Linux

Linux
OS X
Windows

Linux

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

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

yes

Full-featured ANSI SQL support

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

Graphite protocol
HTTP REST
Telnet API

JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

All languages supporting JDBC/ODBC

All languages supporting JDBC/ODBC/ADO.Net

Java
JavaScript

Node.js
PHP
Python

C
C++

Java
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Java Stored Procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication between multi datacenters

selectable replication factor

based on Cassandra

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

fine grained access rights according to SQL-standard

simple password-based access control

Kerberos, SSL and role based access

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

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

Real-Time Performance and Health Monitoring Using Netdata
2 September 2019, CNX Software

provided by Google News

China's answer to Snowflake is shaping as data demands upgrade
8 September 2021, PingWest

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

Share this page