DBMS > Apache Impala vs. Datomic vs. H2GIS vs. IBM Cloudant

System Properties Comparison Apache Impala vs. Datomic vs. H2GIS vs. IBM Cloudant

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Spatial extension of H2

Database as a Service offering based on Apache CouchDB

Primary database model

Relational DBMS

Spatial DBMS

Document store

Secondary database models

Document store

Relational DBMS

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Trend Chart

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

Website

impala.apache.org

www.datomic.com

www.h2gis.org

www.ibm.com/products/cloudant

Technical documentation

impala.apache.org/impala-docs.html

docs.datomic.com

www.h2gis.org/docs/home

cloud.ibm.com/docs/Cloudant

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Cognitect

CNRS

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Initial release

2013

2012

2013

2010

Current release

4.1.0, June 2022

1.0.6735, June 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

limited edition free

Open Source

LGPL 3.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java, Clojure

Java

Erlang

Server operating systems

Linux

All OS with a Java VM

hosted

Data scheme

yes

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

yes

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

Clojure
Java

Java

C#
Java
JavaScript
Objective-C
PHP
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Transaction Functions

yes

based on H2

View functions (Map-Reduce) in JavaScript

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

But extensive use of caching in the application peers

yes

based on H2

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a document possible

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Optimistic locking

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

based on H2

Access rights for users can be defined per database

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