DBMS > GeoMesa vs. Heroic vs. MariaDB vs. OpenTSDB vs. Sphinx

System Properties Comparison GeoMesa vs. Heroic vs. MariaDB vs. OpenTSDB vs. Sphinx

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

MySQL application compatible open source RDBMS, enhanced with high availability, security, interoperability and performance capabilities. MariaDB ColumnStore provides a column-oriented storage engine and MariaDB Xpand supports distributed SQL.

Scalable Time Series DBMS based on HBase

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Secondary database models

Document store
Graph DBMS

with OQGraph storage engine
Spatial DBMS

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

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	93.21
Rank	#13	Overall
	#9	Relational DBMS

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

www.geomesa.org

github.com/spotify/heroic

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

opentsdb.net

sphinxsearch.com

Technical documentation

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

spotify.github.io/heroic

mariadb.com/kb/en/library

opentsdb.net/docs/build/html/index.html

sphinxsearch.com/docs

Developer

CCRi and others

Spotify

MariaDB Corporation Ab (MariaDB Enterprise),
MariaDB Foundation (community MariaDB Server)

The lead developer Monty Widenius is the original author of MySQL

currently maintained by Yahoo and other contributors

Sphinx Technologies Inc.

Initial release

2014

2009

Fork of MySQL, which was first released in 1995

2011

2001

Current release

4.0.5, February 2024

11.3.2, February 2024

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache 2.0

Open Source

GPL version 2, commercial enterprise subscription available

Open Source

LGPL

Open Source

GPL version 2, commercial licence available

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 C++

Java

C++

Server operating systems

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

Linux
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Dynamic columns are supported

schema-free

yes

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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

full-text index on all search fields

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language (SphinxQL)

APIs and other access methods

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

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API
Telnet API

Proprietary protocol

Supported programming languages

Ada
C
C#
C++
D
Eiffel
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Erlang
Go
Java
Python
R
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

PL/SQL compatibility added with version 10.3

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

several options for horizontal partitioning and Sharding

Sharding

based on HBase

Sharding

Partitioning is done manually, search queries against distributed index is supported

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

none

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

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

not for in-memory storage engine

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

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

depending on storage layer

yes

with MEMORY storage engine

User concepts

Access control

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

Web, SaaS and Cloud operational applications that require high availability, scalability...
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Key customers

Deutsche Bank, DBS Bank, Nasdaq, Red Hat, ServiceNow, Verizon and Walgreens Featured...
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Market metrics

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Licensing and pricing models

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