DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Couchbase vs. Manticore Search vs. Oracle Rdb vs. Vitess

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Couchbase vs. Manticore Search vs. Oracle Rdb vs. Vitess

Editorial information provided by DB-Engines

Name

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

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

Multi-storage database for search, including full-text search.

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

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

Time Series DBMS

using the Manticore Columnar Library

Document store
Spatial DBMS

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

Score	0.79
Rank	#213	Overall
	#101	Relational DBMS

Score	16.74
Rank	#33	Overall
	#5	Document stores

Score	0.23
Rank	#301	Overall
	#21	Search engines

Score	1.04
Rank	#184	Overall
	#84	Relational DBMS

Score	0.86
Rank	#202	Overall
	#95	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

www.couchbase.com

manticoresearch.com

www.oracle.com/database/technologies/related/rdb.html

vitess.io

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

docs.couchbase.com

manual.manticoresearch.com

www.oracle.com/database/technologies/related/rdb-doc.html

vitess.io/docs

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Couchbase, Inc.

Manticore Software

Oracle, originally developed by Digital Equipment Corporation (DEC)

The Linux Foundation, PlanetScale

Initial release

2016

2011

2017

1984

2013

Current release

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

6.0, February 2023

7.4.1.1, 2021

15.0.2, December 2022

License

Commercial or Open Source

commercial

Open Source

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

Open Source

GPL version 2

commercial

Open Source

Apache Version 2.0, commercial licenses available

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

C++

Server operating systems

hosted

Linux
OS X
Windows

FreeBSD
Linux
macOS
Windows

HP Open VMS

Docker
Linux
macOS

Data scheme

yes

schema-free

Fixed schema

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

yes

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

yes

Can index from XML

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes

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

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

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

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

C
Java
Perl
Python
R

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

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

Server-side scripts

Stored procedures

yes

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

user defined functions

yes

proprietary syntax

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Automatic Sharding

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication

including cross data center replication
Source-replica replication

Synchronous replication based on Galera library

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

yes, on a single node

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

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

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

Users with fine-grained authorization concept

no user groups or roles

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