DBMS > Apache Impala vs. FatDB vs. KeyDB vs. Riak KV vs. SiteWhere

System Properties Comparison Apache Impala vs. FatDB vs. KeyDB vs. Riak KV vs. SiteWhere

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

Analytic DBMS for Hadoop

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

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Distributed, fault tolerant key-value store

M2M integration platform for persisting/querying time series data

Primary database model

Relational DBMS

Document store
Key-value store

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Time Series DBMS

Secondary database models

Document store

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

impala.apache.org

github.com/Snapchat/KeyDB
keydb.dev

github.com/sitewhere/sitewhere

Technical documentation

impala.apache.org/impala-docs.html

docs.keydb.dev

www.tiot.jp/riak-docs/riak/kv/latest

sitewhere1.sitewhere.io/index.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

FatCloud

EQ Alpha Technology Ltd.

OpenSource, formerly Basho Technologies

SiteWhere

Initial release

2013

2012

2019

2009

2010

Current release

4.1.0, June 2022

3.2.0, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

BSD-3

Open Source

Apache version 2, commercial enterprise edition

Open Source

Common Public Attribution License Version 1.0

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

C++

Erlang

Java

Server operating systems

Linux

Windows

Linux

Linux
OS X

Linux
OS X
Windows

Data scheme

yes

schema-free

predefined scheme

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

by using the Redis Search module

restricted

SQL

Support of SQL

SQL-like DML and DDL statements

Via inetgration in SQL Server

APIs and other access methods

JDBC
ODBC

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

Proprietary protocol

RESP - REdis Serialization Protoco

HTTP API
Native Erlang Interface

HTTP REST

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

via applications

Lua

Erlang

Triggers

yes

via applications

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between data sets can be stored

Transaction concepts

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

Optimistic locking, atomic execution of commands blocks and scripts

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Can implement custom security layer via applications

simple password-based access control and ACL

yes, using Riak Security

Users with fine-grained authorization concept

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