DBMS > AgensGraph vs. Amazon CloudSearch vs. Couchbase vs. EXASOL

System Properties Comparison AgensGraph vs. Amazon CloudSearch vs. Couchbase vs. EXASOL

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Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Primary database model

Graph DBMS
Relational DBMS

Search engine

Document store

Relational DBMS

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	1.81
Rank	#137	Overall
	#12	Search engines

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Website

bitnine.net/agensgraph

aws.amazon.com/cloudsearch

www.couchbase.com

www.exasol.com

Technical documentation

bitnine.net/documentation

docs.aws.amazon.com/cloudsearch

docs.couchbase.com

www.exasol.com/resources

Developer

Bitnine Global Inc.

Amazon

Couchbase, Inc.

Exasol

Initial release

2016

2012

2011

2000

Current release

2.1, December 2018

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

commercial

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++, Go and Erlang

Server operating systems

Linux
OS X
Windows

hosted

Linux
OS X
Windows

Data scheme

depending on used data model

yes

schema-free

yes

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

yes

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

APIs and other access methods

Cypher Query Language
JDBC

HTTP API

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

.Net
JDBC
ODBC
WebSocket

Supported programming languages

C
Java
JavaScript
Python

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Java
Lua
Python
R

Server-side scripts

Stored procedures

yes

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

user defined functions

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

yes

automatic partitioning across Amazon Search Instance as required

Automatic Sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

managed transparently by AWS

Multi-source replication

including cross data center replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

Ephemeral buckets

yes

User concepts

Access control

fine grained access rights according to SQL-standard

authentication via encrypted signatures

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Access rights for users, groups and roles according to SQL-standard

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