DBMS > EJDB vs. Fauna vs. Microsoft SQL Server vs. TerarkDB vs. YottaDB

System Properties Comparison EJDB vs. Fauna vs. Microsoft SQL Server vs. TerarkDB vs. YottaDB

Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

Microsofts flagship relational DBMS

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

A fast and solid embedded Key-value store

Primary database model

Document store

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Relational DBMS

Key-value store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

using the Octo plugin

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

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	1.55
Rank	#151	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

github.com/Softmotions/ejdb

fauna.com

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

github.com/bytedance/terarkdb

yottadb.com

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

docs.fauna.com

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

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

yottadb.com/resources/documentation

Developer

Softmotions

Fauna, Inc.

Microsoft

ByteDance, originally Terark

YottaDB, LLC

Initial release

2012

2014

1989

2016

2001

Current release

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

GPLv2

commercial

restricted free version is available

commercial

restricted open source version available

Open Source

AGPL 3.0

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Scala

C++

Server operating systems

server-less

hosted

Linux
Windows

Docker
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

by using the Octo plugin

APIs and other access methods

in-process shared library

RESTful HTTP API

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

C++ API
Java API

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

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

C++
Java

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

user defined functions

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

consistent hashing

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

yes, but depending on the SQL-Server Edition

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

Identity management, authentication, and access control

fine grained access rights according to SQL-standard

Users and groups based on OS-security mechanisms

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