DBMS > Apache Druid vs. GeoSpock vs. Infobright vs. SQLite

System Properties Comparison Apache Druid vs. GeoSpock vs. Infobright vs. SQLite

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Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Spatial and temporal data processing engine for extreme data scale

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	2.85
Rank	#96	Overall
	#50	Relational DBMS
	#6	Time Series DBMS

Score	0.88
Rank	#198	Overall
	#92	Relational DBMS

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Website

druid.apache.org

geospock.com

ignitetech.com/softwarelibrary/infobrightdb

www.sqlite.org

Technical documentation

druid.apache.org/docs/latest/design

www.sqlite.org/docs.html

Developer

Apache Software Foundation and contributors

GeoSpock

Ignite Technologies Inc.; formerly InfoBright Inc.

Dwayne Richard Hipp

Initial release

2012

2005

2000

Current release

30.0.0, June 2024

2.0, September 2019

3.46.1 (13 August 2024), August 2024

License

Commercial or Open Source

Open Source

Apache license v2

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Java, Javascript

Server operating systems

Linux
OS X
Unix

hosted

Linux
Windows

server-less

Data scheme

yes

schema-less columns are supported

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

temporal, categorical

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

SQL for querying

ANSI SQL for query only (using Presto)

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC

ADO.NET
JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Automatic sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

via file-system locks

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

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Access rights for users can be defined per table

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

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