DBMS > Apache Impala vs. H2GIS vs. Heroic vs. Realm vs. SAP HANA

System Properties Comparison Apache Impala vs. H2GIS vs. Heroic vs. Realm vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Spatial extension of H2

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Secondary database models

Document store

Relational DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

impala.apache.org

www.h2gis.org

github.com/spotify/heroic

realm.io

www.sap.com/products/hana.html

Technical documentation

impala.apache.org/impala-docs.html

www.h2gis.org/docs/home

spotify.github.io/heroic

realm.io/docs

help.sap.com/hana

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

CNRS

Spotify

Realm, acquired by MongoDB in May 2019

SAP

Initial release

2013

2014

2010

Current release

4.1.0, June 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

LGPL 3.0

Open Source

Apache 2.0

Open Source

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Server operating systems

Linux

Android
Backend: server-less
iOS
Windows

Appliance or cloud-service

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

via Elasticsearch

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

Java

.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

runs within the applications so server-side scripts are unnecessary

SQLScript, R

Triggers

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

based on H2

yes

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

Eventual Consistency
Immediate 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

In-Memory realm

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

based on H2

yes

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