DBMS > IBM Cloudant vs. JaguarDB vs. Microsoft Azure Table Storage vs. Pinecone vs. Weaviate

System Properties Comparison IBM Cloudant vs. JaguarDB vs. Microsoft Azure Table Storage vs. Pinecone vs. Weaviate

Editorial information provided by DB-Engines

Name

Description

Database as a Service offering based on Apache CouchDB

Performant, highly scalable DBMS for AI and IoT applications

A Wide Column Store for rapid development using massive semi-structured datasets

A managed, cloud-native vector database

An AI-native realtime vector database engine that integrates scalable machine learning models.

Primary database model

Document store

Key-value store
Vector DBMS

Wide column store

Vector DBMS

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

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

www.ibm.com/products/cloudant

www.jaguardb.com

azure.microsoft.com/en-us/services/storage/tables

www.pinecone.io

github.com/weaviate/weaviate
weaviate.io

Technical documentation

cloud.ibm.com/docs/Cloudant

www.jaguardb.com/support.html

docs.pinecone.io/docs/overview

weaviate.io/developers/weaviate

Developer

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

DataJaguar, Inc.

Microsoft

Pinecone Systems, Inc

Weaviate B.V.

Initial release

2010

2015

2012

2019

Current release

3.3 July 2023

1.19, May 2023

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

commercial

Open Source

commercial license available with Weaviate Enterprise

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

C++

the server part. Clients available in other languages

Server operating systems

hosted

Linux

hosted

Data scheme

schema-free

yes

schema-free

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

String, Number, Boolean

yes

string, int, float, geo point, date, cross reference, fuzzy references

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 data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

GraphQL is used as query language

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC

RESTful HTTP API

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Python

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

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

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

atomic operations within a document possible

optimistic locking

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.

yes

User concepts

Access control

Access rights for users can be defined per database

rights management via user accounts

Access rights based on private key authentication or shared access signatures

API Keys
OpenID Connect Discovery

More information provided by the system vendor

Specific characteristics

Weaviate is an open source vector database that is robust, scalable, cloud-native,...
» more

Competitive advantages

Flexible deployment - Free, open source or fully-managed cloud vector database service...
» more

Typical application scenarios

As a database supporting the development of generative AI and semantic search applications...
» more

Key customers

All companies that have data.
» more

Market metrics

As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
» more

Licensing and pricing models

Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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Weaviate, an ANN Database with CRUD support
2 February 2021, Etienne Dilocker, SeMI Technologies (sponsor)

show all

Recent citations in the news

Cloudant Best (and Worst) Practices — Part 1
18 March 2019, IBM

Intro to Enterprise Cloud Storage: How to Set Up a Cloudant Database
1 December 2014, Linux.com

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16 August 2021, IBM

IBM Expands Cloud Database Services with Kubernetes
26 September 2019, EnterpriseAI

IBM to Purchase Cloudant Database as a service (DBaaS) Provider
22 March 2014, App Developer Magazine

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5 May 2015, Microsoft

How to Use C# Azure.Data.Tables SDK with Azure Cosmos DB
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14 January 2019, InfoWorld

How to write data to Azure Table Store with an Azure Function
14 April 2017, Experts Exchange

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8 March 2018, Visual Studio Magazine

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