DBMS > Amazon CloudSearch vs. Amazon Redshift vs. Bangdb vs. Riak TS vs. RocksDB

System Properties Comparison Amazon CloudSearch vs. Amazon Redshift vs. Bangdb vs. Riak TS vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

A hosted search engine service by Amazon with the data stored in Amazons cloud

Large scale data warehouse service for use with business intelligence tools

Converged and high performance database for device data, events, time series, document and graph

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

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

Primary database model

Search engine

Relational DBMS

Document store
Graph DBMS
Time Series DBMS

Time Series DBMS

Key-value store

Secondary database models

Spatial DBMS

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

Score	1.85
Rank	#137	Overall
	#12	Search engines

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

aws.amazon.com/cloudsearch

aws.amazon.com/redshift

bangdb.com

rocksdb.org

Technical documentation

docs.aws.amazon.com/cloudsearch

docs.aws.amazon.com/redshift

docs.bangdb.com

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

github.com/facebook/rocksdb/wiki

Developer

Amazon

Amazon (based on PostgreSQL)

Sachin Sinha, BangDB

Open Source, formerly Basho Technologies

Facebook, Inc.

Initial release

2012

2015

2013

Current release

BangDB 2.0, October 2021

3.0.0, September 2022

8.11.4, April 2024

License

Commercial or Open Source

commercial

Open Source

BSD 3

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

Erlang

C++

Server operating systems

hosted

Linux

Linux
OS X

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

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

all search fields are automatically indexed

restricted

yes

secondary, composite, nested, reverse, geospatial

restricted

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL like support with command line tool

yes, limited

APIs and other access methods

HTTP API

JDBC
ODBC

Proprietary protocol
RESTful HTTP API

HTTP API
Native Erlang Interface

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Java
Python

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

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

Erlang

Triggers

yes, Notifications (with Streaming only)

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

yes

selectable replication factor, Knob for CAP (enterprise version only)

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable consistency, set CAP knob accordingly

Eventual Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

links between datasets can be stored

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes

yes, run db with in-memory only mode

yes

User concepts

Access control

authentication via encrypted signatures

fine grained access rights according to SQL-standard

yes (enterprise version only)

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