DBMS > Drizzle vs. GeoMesa vs. Heroic vs. Kinetica vs. OpenTSDB

System Properties Comparison Drizzle vs. GeoMesa vs. Heroic vs. Kinetica vs. OpenTSDB

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

Fully vectorized database across both GPUs and CPUs

Scalable Time Series DBMS based on HBase

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Website

www.geomesa.org

github.com/spotify/heroic

www.kinetica.com

opentsdb.net

Technical documentation

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

spotify.github.io/heroic

docs.kinetica.com

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

Developer

Drizzle project, originally started by Brian Aker

CCRi and others

Spotify

Kinetica

currently maintained by Yahoo and other contributors

Initial release

2008

2014

2012

2011

Current release

7.2.4, September 2012

5.0.0, May 2024

7.1, August 2021

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache License 2.0

Open Source

Apache 2.0

commercial

Open Source

LGPL

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++

Scala

Java

C, C++

Java

Server operating systems

FreeBSD
Linux
OS X

Linux

Linux
Windows

Data scheme

yes

schema-free

yes

schema-free

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.

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like DML and DDL statements

APIs and other access methods

JDBC

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

JDBC
ODBC
RESTful HTTP API

HTTP API
Telnet API

Supported programming languages

C
C++
Java
PHP

C++
Java
JavaScript (Node.js)
Python

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

Triggers

hooks for callbacks inside the server can be used.

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

Sharding

depending on storage layer

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

depending on storage layer

yes

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 or Eventual Consistency depending on configuration

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

yes

GPU vRAM or System RAM

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

yes

depending on the DBMS used for storage

Access rights for users and roles on table level

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

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Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

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