DBMS > Apache Impala vs. DataFS vs. H2GIS vs. SpaceTime

System Properties Comparison Apache Impala vs. DataFS vs. H2GIS vs. SpaceTime

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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.

Spatial extension of H2

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Primary database model

Relational DBMS

Object oriented DBMS

Spatial DBMS

Secondary database models

Document store

Graph DBMS

Relational DBMS

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

Score	10.63
Rank	#40	Overall
	#24	Relational DBMS

Score	0.02
Rank	#369	Overall
	#18	Object oriented DBMS

Score	0.00
Rank	#385	Overall
	#7	Spatial DBMS

Score	0.00
Rank	#385	Overall
	#7	Spatial DBMS

Website

impala.apache.org

newdatabase.com

www.h2gis.org

www.mireo.com/spacetime

Technical documentation

impala.apache.org/impala-docs.html

dev.mobiland.com/Overview.xsp

www.h2gis.org/docs/home

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Mobiland AG

CNRS

Mireo

Initial release

2013

2018

2013

2020

Current release

4.1.0, June 2022

1.1.263, October 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

LGPL 3.0

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++

Java

C++

Server operating systems

Linux

Windows

Linux

Data scheme

yes

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

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

A subset of ANSI SQL is implemented

APIs and other access methods

JDBC
ODBC

.NET Client API
Proprietary client DLL
WinRT client

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C#
C++
VB.Net

Java

C#
C++
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

based on H2

Triggers

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Proprietary Sharding system

none

Fixed-grid hypercubes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

based on H2

Real-time block device replication (DRBD)

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

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Windows-Profile

yes

based on H2

yes

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More resources

Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
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

provided by Google News

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