DBMS > IBM Cloudant vs. Memcached vs. Snowflake vs. SQream DB vs. Weaviate

System Properties Comparison IBM Cloudant vs. Memcached vs. Snowflake vs. SQream DB vs. Weaviate

Editorial information provided by DB-Engines

Name

Description

Database as a Service offering based on Apache CouchDB

In-memory key-value store, originally intended for caching

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

a GPU-based, columnar RDBMS for big data analytics workloads

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

Primary database model

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

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	18.08
Rank	#32	Overall
	#4	Key-value stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Score	1.52
Rank	#153	Overall
	#6	Vector DBMS

Website

www.ibm.com/products/cloudant

www.memcached.org

www.snowflake.com

sqream.com

github.com/weaviate/weaviate
weaviate.io

Technical documentation

cloud.ibm.com/docs/Cloudant

github.com/memcached/memcached/wiki

docs.snowflake.net/manuals/index.html

docs.sqream.com

weaviate.io/developers/weaviate

Developer

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Snowflake Computing Inc.

SQream Technologies

Weaviate B.V.

Initial release

2010

2003

2014

2017

2019

Current release

1.6.27, May 2024

2022.1.6, December 2022

1.19, May 2023

License

Commercial or Open Source

commercial

Open Source

BSD license

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++, CUDA, Haskell, Java, Scala

Server operating systems

hosted

FreeBSD
Linux
OS X
Unix
Windows

hosted

Linux

Data scheme

schema-free

yes

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

yes

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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.

yes

Secondary indexes

yes

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

SQL

Support of SQL

yes

GraphQL is used as query language

APIs and other access methods

RESTful HTTP/JSON API

Proprietary protocol

CLI Client
JDBC
ODBC

.Net
JDBC
ODBC

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

JavaScript (Node.js)
Python

C++
Java
JavaScript (Node.js)
Python

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

user defined functions

user defined functions in Python

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

horizontal and vertical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

Repcached, a Memcached patch, provides this functionallity

yes

none

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

yes

Transaction concepts

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

atomic operations within a document possible

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.

yes

User concepts

Access control

Access rights for users can be defined per database

yes

using SASL (Simple Authentication and Security Layer) protocol

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

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.