DBMS > IBM Cloudant vs. Lovefield vs. Snowflake vs. SQream DB

System Properties Comparison IBM Cloudant vs. Lovefield vs. Snowflake vs. SQream DB

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Editorial information provided by DB-Engines

Name

Description

Database as a Service offering based on Apache CouchDB

Embeddable relational database for web apps written in pure JavaScript

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

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

Primary database model

Document store

Relational DBMS

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

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Website

www.ibm.com/products/cloudant

google.github.io/lovefield

www.snowflake.com

sqream.com

Technical documentation

cloud.ibm.com/docs/Cloudant

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.snowflake.net/manuals/index.html

docs.sqream.com

Developer

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Google

Snowflake Computing Inc.

SQream Technologies

Initial release

2010

2014

2017

Current release

2.1.12, February 2017

2022.1.6, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

JavaScript

C++, CUDA, Haskell, Java, Scala

Server operating systems

hosted

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

hosted

Linux

Data scheme

schema-free

yes

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

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

RESTful HTTP/JSON API

CLI Client
JDBC
ODBC

.Net
JDBC
ODBC

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

JavaScript

JavaScript (Node.js)
Python

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

user defined functions

user defined functions in Python

Triggers

yes

Using read-only observers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

yes

none

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

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

Access rights for users can be defined per database

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

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