DBMS > IBM Db2 warehouse vs. Lovefield vs. Sequoiadb vs. Snowflake

System Properties Comparison IBM Db2 warehouse vs. Lovefield vs. Sequoiadb vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

Cloud-based data warehousing service

Embeddable relational database for web apps written in pure JavaScript

NewSQL database with distributed OLTP and SQL

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

Primary database model

Relational DBMS

Document store
Relational DBMS

Relational DBMS

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

Score	1.26
Rank	#162	Overall
	#73	Relational DBMS

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	0.42
Rank	#263	Overall
	#41	Document stores
	#121	Relational DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Website

www.ibm.com/products/db2/warehouse

google.github.io/lovefield

www.sequoiadb.com

www.snowflake.com

Technical documentation

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

www.sequoiadb.com/en/index.php?m=Files&a=index

docs.snowflake.net/manuals/index.html

Developer

IBM

Google

Sequoiadb Ltd.

Snowflake Computing Inc.

Initial release

2014

2013

2014

Current release

2.1.12, February 2017

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Server: AGPL; Client: Apache V2

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

JavaScript

C++

Server operating systems

hosted

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

tested with Chrome, Firefox, IE, Safari

Linux

hosted

Data scheme

yes

schema-free

yes

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

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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.

Import/export of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

SQL-like query language

yes

APIs and other access methods

.NET Client API
JDBC
ODBC
OLE DB

proprietary protocol using JSON

CLI Client
JDBC
ODBC

Supported programming languages

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

JavaScript

.Net
C++
Java
PHP
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

PL/SQL, SQL PL

JavaScript

user defined functions

Triggers

yes

Using read-only observers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Document is locked during a transaction

ACID

Concurrency

Support for concurrent manipulation of data

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

fine grained access rights according to SQL-standard

simple password-based access control

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

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