DBMS > Apache Impala vs. H2GIS vs. RavenDB vs. Realm

System Properties Comparison Apache Impala vs. H2GIS vs. RavenDB vs. Realm

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Spatial extension of H2

Open Source Operational and Transactional Enterprise NoSQL Document Database

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Primary database model

Relational DBMS

Spatial DBMS

Document store

Secondary database models

Document store

Relational DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	14.03
Rank	#40	Overall
	#24	Relational DBMS

Score	0.05
Rank	#372	Overall
	#7	Spatial DBMS

Score	3.01
Rank	#101	Overall
	#17	Document stores

Score	7.71
Rank	#52	Overall
	#9	Document stores

Website

Technical documentation

impala.apache.org/impala-docs.html

www.h2gis.org/docs/home

ravendb.net/docs

realm.io/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

CNRS

Hibernating Rhinos

Realm, acquired by MongoDB in May 2019

Initial release

2013

2010

2014

Current release

4.1.0, June 2022

5.4, July 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

LGPL 3.0

Open Source

AGPL version 3, commercial license available

Open Source

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

Server operating systems

Linux

Linux
macOS
Raspberry Pi
Windows

Android
Backend: server-less
iOS
Windows

Data scheme

yes

schema-free

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

SQL-like query language (RQL)

APIs and other access methods

JDBC
ODBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

Java

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

based on H2

yes

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

based on H2

Multi-source replication

none

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

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

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

In-Memory realm

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

based on H2

Authorization levels configured per client per database

yes

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More resources

DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

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Recent citations in the news

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

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28 November 2017, Datanami

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