DBMS > BoltDB vs. FileMaker vs. Microsoft Azure Cosmos DB vs. RethinkDB vs. SwayDB

System Properties Comparison BoltDB vs. FileMaker vs. Microsoft Azure Cosmos DB vs. RethinkDB vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

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

Globally distributed, horizontally scalable, multi-model database service

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Key-value store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Document store

Key-value store

Secondary database models

Spatial DBMS

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

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	48.20
Rank	#20	Overall
	#14	Relational DBMS

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

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

github.com/boltdb/bolt

www.claris.com/filemaker

azure.microsoft.com/services/cosmos-db

rethinkdb.com

swaydb.simer.au

Technical documentation

www.claris.com/resources/documentation

learn.microsoft.com/azure/cosmos-db

rethinkdb.com/docs

Developer

Claris

a subsidiary of Apple

Microsoft

The Linux Foundation

since July 2017

Simer Plaha

Initial release

2013

1983

2014

2009

2018

Current release

19.4.1, November 2021

2.4.1, August 2020

License

Commercial or Open Source

Open Source

MIT License

commercial

Open Source

Apache Version 2

Open Source

GNU Affero GPL V3.0

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

C++

Scala

Server operating systems

BSD
Linux
OS X
Solaris
Windows

iOS

client part only
Linux
OS X
Windows

hosted

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

yes

string, binary, float, bool, date, geometry

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

APIs and other access methods

Filemaker WebDirect
JDBC
ODBC

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

Supported programming languages

PHP

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

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

yes

JavaScript

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

range based

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication, warm standby

since Version 14

yes

Implicit feature of the cloud service

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

Multi-item ACID transactions with snapshot isolation within a partition

Atomic single-document operations

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

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.

yes

User concepts

Access control

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

Access rights can be defined down to the item level

yes

users and table-level permissions

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