DBMS > Oracle NoSQL vs. Sequoiadb vs. Snowflake vs. TempoIQ vs. Teradata

System Properties Comparison Oracle NoSQL vs. Sequoiadb vs. Snowflake vs. TempoIQ vs. Teradata

Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

NewSQL database with distributed OLTP and SQL

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

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Document store
Key-value store
Relational DBMS

Document store
Relational DBMS

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Website

www.oracle.com/database/nosql/technologies/nosql

www.sequoiadb.com

www.snowflake.com

tempoiq.com (offline)

www.teradata.com

Technical documentation

docs.oracle.com/en/database/other-databases/nosql-database/index.html

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

docs.snowflake.net/manuals/index.html

docs.teradata.com

Developer

Oracle

Sequoiadb Ltd.

Snowflake Computing Inc.

TempoIQ

Teradata

Initial release

2011

2013

2014

2012

1984

Current release

24.1, May 2024

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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

Java

C++

Server operating systems

Linux
Solaris SPARC/x86

Linux

hosted

hosted
Linux

Data scheme

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

schema-free

yes

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

schema-free

yes

Typing

predefined data types such as float or date

optional

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.

yes

Secondary indexes

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

yes

SQL 2016 + extensions

APIs and other access methods

RESTful HTTP API

proprietary protocol using JSON

CLI Client
JDBC
ODBC

HTTP API

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

C
C#
Go
Java
JavaScript (Node.js)
Python

.Net
C++
Java
PHP
Python

JavaScript (Node.js)
Python

C#
Java
JavaScript

Node.js
Python
Ruby

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

JavaScript

user defined functions

yes

UDFs, stored procedures, table functions in parallel

Triggers

similar concept for controling cloud resources

yes

Realtime Alerts

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Source-replica replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

depending on configuration

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

configurable

ACID within a storage node (=shard)

Document is locked during a transaction

ACID

Concurrency

Support for concurrent manipulation of data

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

off heap cache

yes

User concepts

Access control

Access rights for users and roles

simple password-based access control

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

simple authentication-based access control

fine grained access rights according to SQL-standard

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