DBMS > FatDB vs. Hazelcast vs. InfinityDB vs. Memcached vs. RocksDB

System Properties Comparison FatDB vs. Hazelcast vs. InfinityDB vs. Memcached vs. RocksDB

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.

A widely adopted in-memory data grid

A Java embedded Key-Value Store which extends the Java Map interface

In-memory key-value store, originally intended for caching

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Document store
Key-value store

Key-value store

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	6.87
Rank	#55	Overall
	#6	Key-value stores

Score	0.07
Rank	#359	Overall
	#54	Key-value stores

Score	20.74
Rank	#32	Overall
	#4	Key-value stores

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Website

Technical documentation

hazelcast.org/imdg/docs

boilerbay.com/infinitydb/manual

github.com/memcached/memcached/wiki

github.com/facebook/rocksdb/wiki

Developer

FatCloud

Hazelcast

Boiler Bay Inc.

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Facebook, Inc.

Initial release

2012

2008

2002

2003

2013

Current release

5.3.6, November 2023

4.0

1.6.25, March 2024

8.11.4, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

BSD license

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Server operating systems

Windows

All OS with a Java VM

FreeBSD
Linux
OS X
Unix
Windows

Linux

Data scheme

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

the object must implement a serialization strategy

Secondary indexes

yes

manual creation possible, using inversions based on multi-value capability

SQL

Support of SQL

Via inetgration in SQL Server

SQL-like query language

APIs and other access methods

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

JCache
JPA
Memcached protocol
RESTful HTTP API

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

Proprietary protocol

C++ API
Java API

Supported programming languages

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

Java

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

via applications

yes

Event Listeners, Executor Services

Triggers

yes

via applications

yes

Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Replicated Map

none

Repcached, a Memcached patch, provides this functionallity

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 selectable by user

Raft Consensus Algorithm

Immediate Consistency

READ-COMMITTED or SERIALIZED

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

one or two-phase-commit; repeatable reads; read commited

ACID

Optimistic locking for transactions; no isolation for bulk loads

yes

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

Role-based access control

yes

using SASL (Simple Authentication and Security Layer) protocol

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