DBMS > FatDB vs. Microsoft Azure AI Search vs. RavenDB vs. TimesTen vs. Tkrzw

System Properties Comparison FatDB vs. Microsoft Azure AI Search vs. RavenDB vs. TimesTen vs. Tkrzw

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

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

Search-as-a-service for web and mobile app development

Open Source Operational and Transactional Enterprise NoSQL Document Database

In-Memory RDBMS compatible to Oracle

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Document store
Key-value store

Secondary database models

Vector DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

azure.microsoft.com/en-us/services/search

ravendb.net

www.oracle.com/database/technologies/related/timesten.html

dbmx.net/tkrzw

Technical documentation

learn.microsoft.com/en-us/azure/search

ravendb.net/docs

docs.oracle.com/database/timesten-18.1

Developer

FatCloud

Microsoft

Hibernating Rhinos

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Mikio Hirabayashi

Initial release

2012

2015

2010

1998

2020

Current release

5.4, July 2022

11 Release 2 (11.2.2.8.0)

0.9.3, August 2020

License

Commercial or Open Source

commercial

Open Source

AGPL version 3, commercial license available

commercial

Open Source

Apache Version 2.0

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

hosted

Linux
macOS
Raspberry Pi
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
macOS

Data scheme

schema-free

yes

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

SQL

Support of SQL

Via inetgration in SQL Server

SQL-like query language (RQL)

yes

APIs and other access methods

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

RESTful HTTP API

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C#
Java
JavaScript
Python

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C++
Java
PL/SQL

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

via applications

yes

PL/SQL

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Implicit feature of the cloud service

Multi-source replication

Multi-source replication
Source-replica replication

none

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

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID, Cluster-wide transaction available

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using specific database classes

User concepts

Access control

Can implement custom security layer via applications

yes

using Azure authentication

Authorization levels configured per client per database

fine grained access rights according to SQL-standard

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