DBMS > FileMaker vs. GeoMesa vs. LevelDB vs. Microsoft Azure Cosmos DB vs. SQLite

System Properties Comparison FileMaker vs. GeoMesa vs. LevelDB vs. Microsoft Azure Cosmos DB vs. SQLite

Editorial information provided by DB-Engines

Name

Description

FileMaker is a cross-platform RDBMS that includes a GUI frontend.

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

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

Globally distributed, horizontally scalable, multi-model database service

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

Spatial DBMS

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	48.20
Rank	#20	Overall
	#14	Relational DBMS

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

www.claris.com/filemaker

www.geomesa.org

github.com/google/leveldb

azure.microsoft.com/services/cosmos-db

www.sqlite.org

Technical documentation

www.claris.com/resources/documentation

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

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

learn.microsoft.com/azure/cosmos-db

www.sqlite.org/docs.html

Developer

Claris

a subsidiary of Apple

CCRi and others

Google

Microsoft

Dwayne Richard Hipp

Initial release

1983

2014

2011

2014

2000

Current release

19.4.1, November 2021

4.0.5, February 2024

1.23, February 2021

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

Open Source

BSD

commercial

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Scala

C++

Server operating systems

iOS

client part only
Linux
OS X
Windows

Illumos
Linux
OS X
Windows

hosted

server-less

Data scheme

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

JSON types

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

A http query request can return the data in XML format

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

via plugins

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

Filemaker WebDirect
JDBC
ODBC

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

PHP

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

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

yes

JavaScript

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

none

depending on storage layer

none

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication, warm standby

since Version 14

depending on storage layer

none

yes

Implicit feature of the cloud service

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

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

simple rights management via user accounts and connection to external directory services

yes

depending on the DBMS used for storage

Access rights can be defined down to the item level

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