DBMS > GeoMesa vs. Heroic vs. Impala vs. SAP Advantage Database Server

System Properties Comparison GeoMesa vs. Heroic vs. Impala vs. SAP Advantage Database Server

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Editorial information provided by DB-Engines

Name

Description

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

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

Analytic DBMS for Hadoop

Low-cost RDBMS with access to ISAM and FoxPro data structures

Primary database model

Spatial DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store

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

Score	0.75
Rank	#203	Overall
	#3	Spatial DBMS

Score	0.25
Rank	#280	Overall
	#22	Time Series DBMS

Score	17.79
Rank	#40	Overall
	#25	Relational DBMS

Score	3.66
Rank	#91	Overall
	#48	Relational DBMS

Website

www.geomesa.org

spotify.github.io/heroic/#!/index

www.cloudera.com/products/open-source/apache-hadoop/impala.html

www.sap.com/products/advantage-database-server.html

Technical documentation

www.geomesa.org/documentation/stable/user/index.html

spotify.github.io/heroic/#!/docs/overview

docs.cloudera.com/documentation/enterprise/latest/topics/impala.html

Developer

CCRi and others

Spotify

Cloudera

Sybase, SAP

Initial release

2014

2013

1993

Current release

3.2.0, April 2021

4.0.0, July 2021

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache 2.0

Open Source

Apache Version 2

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

Scala

Java

C++

Server operating systems

Linux

Linux
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

via Elasticsearch

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

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

JDBC
ODBC

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

All languages supporting JDBC/ODBC

Delphi
Perl
PHP

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

yes

selectable replication factor

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

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

depending on storage layer

Eventual Consistency
Immediate Consistency

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

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.

depending on storage layer

caching of (temporary) tables can be configured

User concepts

Access control

yes

depending on the DBMS used for storage

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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