DBMS > Apache Druid vs. GeoMesa vs. PostgreSQL vs. SQLite

System Properties Comparison Apache Druid vs. GeoMesa vs. PostgreSQL vs. SQLite

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Editorial information provided by DB-Engines

Name

Description

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

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

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS
Time Series DBMS

Spatial DBMS

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Relational DBMS

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	636.25
Rank	#4	Overall
	#4	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

Technical documentation

druid.apache.org/docs/latest/design

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

www.postgresql.org/docs

www.sqlite.org/docs.html

Developer

Apache Software Foundation and contributors

CCRi and others

PostgreSQL Global Development Group

www.postgresql.org/developer

Dwayne Richard Hipp

Initial release

2012

2014

1989

1989: Postgres, 1996: PostgreSQL

2000

Current release

29.0.1, April 2024

5.0.0, May 2024

16.3, May 2024

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache License 2.0

Open Source

BSD

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

Java

Scala

Server operating systems

Linux
OS X
Unix

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
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.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

yes

standard with numerous extensions

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
RESTful HTTP/JSON API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
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

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

depending on storage layer

partitioning by range, list and (since PostgreSQL 11) by hash

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

depending on storage layer

Source-replica replication

other methods possible by using 3rd party extensions

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

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.

depending on storage layer

yes

User concepts

Access control

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

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard

More information provided by the system vendor

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