DBMS > FileMaker vs. HugeGraph vs. Microsoft SQL Server vs. PouchDB vs. YDB

System Properties Comparison FileMaker vs. HugeGraph vs. Microsoft SQL Server vs. PouchDB vs. YDB

Editorial information provided by DB-Engines

Name

Description

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

A fast-speed and highly-scalable Graph DBMS

Microsofts flagship relational DBMS

JavaScript DBMS with an API inspired by CouchDB

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Document store
Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	48.20
Rank	#20	Overall
	#14	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	0.35
Rank	#278	Overall
	#43	Document stores
	#127	Relational DBMS

Website

www.claris.com/filemaker

github.com/hugegraph
hugegraph.apache.org

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

pouchdb.com

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

www.claris.com/resources/documentation

hugegraph.apache.org/docs

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

pouchdb.com/guides

ydb.tech/en/docs

Developer

Claris

a subsidiary of Apple

Baidu

Microsoft

Apache Software Foundation

Yandex

Initial release

1983

2018

1989

2012

2019

Current release

19.4.1, November 2021

0.9

SQL Server 2022, November 2022

7.1.1, June 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

restricted free version is available

Open Source

Apache 2.0; commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

JavaScript

Server operating systems

iOS

client part only
Linux
OS X
Windows

Linux
macOS
Unix

Linux
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Linux

Data scheme

yes

schema-free

Flexible Schema (defined schema, partial schema, schema free)

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

A http query request can return the data in XML format

yes

Secondary indexes

yes

also supports composite index and range index

yes

via views

yes

SQL

Support of SQL

yes

via plugins

yes

SQL-like query language (YQL)

APIs and other access methods

Filemaker WebDirect
JDBC
ODBC

Java API
RESTful HTTP API
TinkerPop Gremlin

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

HTTP REST

only for PouchDB Server
JavaScript API

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

PHP

Groovy
Java
Python

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

JavaScript

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

yes

asynchronous Gremlin script jobs

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

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

depending on used storage backend, e.g. Cassandra and HBase

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

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication, warm standby

since Version 14

yes

depending on used storage backend, e.g. Cassandra and HBase

yes, but depending on the SQL-Server Edition

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

Users, roles and permissions

fine grained access rights according to SQL-standard

Access rights defined for Yandex Cloud users

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