DBMS > GeoMesa vs. IBM Db2 Event Store vs. LevelDB vs. Microsoft SQL Server vs. PostGIS

System Properties Comparison GeoMesa vs. IBM Db2 Event Store vs. LevelDB vs. Microsoft SQL Server vs. PostGIS

Editorial information provided by DB-Engines

Name

Description

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

Distributed Event Store optimized for Internet of Things use cases

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Microsofts flagship relational DBMS

Spatial extension of PostgreSQL

Primary database model

Spatial DBMS

Event Store
Time Series DBMS

Key-value store

Relational DBMS

Spatial DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Website

www.geomesa.org

www.ibm.com/products/db2-event-store

github.com/google/leveldb

www.microsoft.com/en-us/sql-server

postgis.net

Technical documentation

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

www.ibm.com/docs/en/db2-event-store

github.com/google/leveldb/blob/main/doc/index.md

learn.microsoft.com/en-US/sql/sql-server

postgis.net/documentation

Developer

CCRi and others

IBM

Google

Microsoft

Initial release

2014

2017

2011

1989

2005

Current release

5.0.0, May 2024

2.0

1.23, February 2021

SQL Server 2022, November 2022

3.4.2, February 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

free developer edition available

Open Source

BSD

commercial

restricted free version is available

Open Source

GPL v2.0

Cloud-based only

Only available as a cloud service

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Implementation language

Scala

C and C++

C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Illumos
Linux
OS X
Windows

Linux
Windows

Data scheme

yes

schema-free

yes

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

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

yes

based on PostgreSQL

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

Active-active shard replication

none

yes, but depending on the SQL-Server Edition

yes

based on PostgreSQL

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

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

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

with automatic compression on writes

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

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard

yes

based on PostgreSQL

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