DBMS > EJDB vs. FatDB vs. HBase vs. Microsoft SQL Server vs. Snowflake

System Properties Comparison EJDB vs. FatDB vs. HBase vs. Microsoft SQL Server vs. Snowflake

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

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

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Wide-column store based on Apache Hadoop and on concepts of BigTable

Microsofts flagship relational DBMS

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Document store

Document store
Key-value store

Wide column 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	0.27
Rank	#297	Overall
	#44	Document stores

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

github.com/Softmotions/ejdb

hbase.apache.org

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

www.snowflake.com

Technical documentation

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

hbase.apache.org/book.html

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

docs.snowflake.net/manuals/index.html

Developer

Softmotions

FatCloud

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Microsoft

Snowflake Computing Inc.

Initial release

2012

2008

1989

2014

Current release

2.3.4, January 2021

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

GPLv2

commercial

Open Source

Apache version 2

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C++

Server operating systems

server-less

Windows

Linux
Unix
Windows

using Cygwin

Linux
Windows

hosted

Data scheme

schema-free

schema-free, schema definition possible

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

options to bring your own types, AVRO

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

Via inetgration in SQL Server

yes

APIs and other access methods

in-process shared library

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

Java API
RESTful HTTP API
Thrift

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

CLI Client
JDBC
ODBC

Supported programming languages

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

C
C#
C++
Groovy
Java
PHP
Python
Scala

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

via applications

yes

Coprocessors in Java

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

user defined functions

Triggers

yes

via applications

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency or Eventual Consistency

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

Single row ACID (across millions of columns)

ACID

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

Can implement custom security layer via applications

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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