DBMS > GeoMesa vs. Heroic vs. Tibero vs. Warp 10

System Properties Comparison GeoMesa vs. Heroic vs. Tibero vs. Warp 10

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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

A secure RDBMS, designed for easy portability from Oracle

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

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

Score	0.81
Rank	#214	Overall
	#4	Spatial DBMS

Score	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	1.81
Rank	#143	Overall
	#65	Relational DBMS

Score	0.08
Rank	#358	Overall
	#35	Time Series DBMS

Website

www.geomesa.org

github.com/spotify/heroic

us.tmaxsoft.com/products/tibero

www.warp10.io

Technical documentation

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

spotify.github.io/heroic

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

www.warp10.io/content/02_Getting_started

Developer

CCRi and others

Spotify

TmaxSoft

SenX

Initial release

2014

2003

2015

Current release

4.0.5, February 2024

6, April 2015

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache 2.0

commercial

Open Source

Apache License 2.0

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 and Assembler

Java

Server operating systems

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

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.

yes

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

APIs and other access methods

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

HTTP API
Jupyter
WebSocket

Supported programming languages

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

Persistent Stored Procedure (PSM)

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

horizontal partitioning

by range, hash, list or composite

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

yes

Multi-source replication
Source-replica replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Eventual Consistency
Immediate Consistency

Immediate Consistency

based on HBase

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

planned for next version

yes

User concepts

Access control

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

Mandatory use of cryptographic tokens, containing fine-grained authorizations

More information provided by the system vendor

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More resources

DB-Engines blog posts

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6 April 2021, Matthias Gelbmann

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