DBMS > FatDB vs. Hypertable vs. Microsoft Azure Synapse Analytics vs. YottaDB

System Properties Comparison FatDB vs. Hypertable vs. Microsoft Azure Synapse Analytics vs. YottaDB

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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.

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

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

An open source BigTable implementation based on distributed file systems such as Hadoop

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

A fast and solid embedded Key-value store

Primary database model

Document store
Key-value store

Wide column store

Relational DBMS

Key-value store

Secondary database models

Relational DBMS

using the Octo plugin

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

Score	18.98
Rank	#31	Overall
	#19	Relational DBMS

Score	0.21
Rank	#309	Overall
	#43	Key-value stores

Website

azure.microsoft.com/services/synapse-analytics

yottadb.com

Technical documentation

docs.microsoft.com/azure/synapse-analytics

yottadb.com/resources/documentation

Developer

FatCloud

Hypertable Inc.

Microsoft

YottaDB, LLC

Initial release

2012

2009

2016

2001

Current release

0.9.8.11, March 2016

License

Commercial or Open Source

commercial

Open Source

GNU version 3. Commercial license available

commercial

Open Source

AGPL 3.0

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++

Server operating systems

Windows

Linux
OS X
Windows

an inofficial Windows port is available

hosted

Docker
Linux

Data scheme

schema-free

yes

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.

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

Via inetgration in SQL Server

yes

by using the Octo plugin

APIs and other access methods

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

C++ API
Thrift

ADO.NET
JDBC
ODBC

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

C#
Java
PHP

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

Server-side scripts

Stored procedures

yes

via applications

Transact SQL

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

selectable replication factor on file system level

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

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

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

yes

Users and groups based on OS-security mechanisms

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