DBMS > IBM Cloudant vs. Pinecone vs. Postgres-XL vs. Snowflake

System Properties Comparison IBM Cloudant vs. Pinecone vs. Postgres-XL vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

Database as a Service offering based on Apache CouchDB

A managed, cloud-native vector database

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Document store

Vector DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	3.23
Rank	#92	Overall
	#3	Vector DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

www.ibm.com/products/cloudant

www.pinecone.io

www.postgres-xl.org

www.snowflake.com

Technical documentation

cloud.ibm.com/docs/Cloudant

docs.pinecone.io/docs/overview

www.postgres-xl.org/documentation

docs.snowflake.net/manuals/index.html

Developer

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Pinecone Systems, Inc

Snowflake Computing Inc.

Initial release

2010

2019

2014

since 2012, originally named StormDB

2014

Current release

10 R1, October 2018

License

Commercial or Open Source

commercial

Open Source

Mozilla public license

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

Erlang

Server operating systems

hosted

Linux
macOS

hosted

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

String, Number, 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

XML type, but no XML query functionality

yes

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

yes

APIs and other access methods

RESTful HTTP/JSON API

RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

CLI Client
JDBC
ODBC

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a document possible

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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.

User concepts

Access control

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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