DBMS > Amazon CloudSearch vs. CrateDB vs. MySQL vs. Oracle NoSQL

System Properties Comparison Amazon CloudSearch vs. CrateDB vs. MySQL vs. Oracle NoSQL

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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

Distributed Database based on Lucene

Widely used open source RDBMS

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Search engine

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Relational DBMS

Key/Value like access via memcached API

Document store
Key-value store
Relational DBMS

Secondary database models

Relational DBMS

Document store
Spatial DBMS

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

Score	1.86
Rank	#133	Overall
	#12	Search engines

Score	0.69
Rank	#226	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#11	Vector DBMS

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Score	3.07
Rank	#86	Overall
	#15	Document stores
	#11	Key-value stores
	#47	Relational DBMS

Website

aws.amazon.com/cloudsearch

cratedb.com

www.mysql.com

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

docs.aws.amazon.com/cloudsearch

cratedb.com/docs

dev.mysql.com/doc

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

Amazon

Crate

Oracle

since 2010, originally MySQL AB, then Sun

Oracle

Initial release

2012

2013

1995

2011

Current release

5.8.1, August 2024

9.0.0, July 2024

24.1, May 2024

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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

Java

C and C++

Java

Server operating systems

hosted

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Solaris SPARC/x86

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

optional

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

Secondary indexes

yes

all search fields are automatically indexed

yes

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

with proprietary extensions

SQL-like DML and DDL statements

APIs and other access methods

HTTP API

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

RESTful HTTP API

Supported programming languages

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions (Javascript)

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

Configurable replication on table/partition-level

Multi-source replication
Source-replica replication

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

unique row identifiers can be used for implementing an optimistic concurrency control strategy

ACID

not for MyISAM storage engine

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

off heap cache

User concepts

Access control

authentication via encrypted signatures

rights management via user accounts

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and roles

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