DBMS > Amazon CloudSearch vs. Kinetica vs. RocksDB vs. Tkrzw

System Properties Comparison Amazon CloudSearch vs. Kinetica vs. RocksDB vs. Tkrzw

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Editorial information provided by DB-Engines

Name

Description

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

Fully vectorized database across both GPUs and CPUs

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

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

Search engine

Relational DBMS

Key-value store

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	1.81
Rank	#137	Overall
	#12	Search engines

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

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

Website

aws.amazon.com/cloudsearch

www.kinetica.com

rocksdb.org

dbmx.net/tkrzw

Technical documentation

docs.aws.amazon.com/cloudsearch

docs.kinetica.com

github.com/facebook/rocksdb/wiki

Developer

Amazon

Kinetica

Facebook, Inc.

Mikio Hirabayashi

Initial release

2012

2013

2020

Current release

7.1, August 2021

9.2.1, May 2024

0.9.3, August 2020

License

Commercial or Open Source

commercial

Open Source

BSD

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, C++

C++

Server operating systems

hosted

Linux

Linux
macOS

Data scheme

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

all search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

HTTP API

JDBC
ODBC
RESTful HTTP API

C++ API
Java API

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

C
C++
Go
Java
Perl
Python
Ruby

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

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

GPU vRAM or System RAM

yes

using specific database classes

User concepts

Access control

authentication via encrypted signatures

Access rights for users and roles on table level

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