DBMS > Google Search Appliance vs. Microsoft Azure Cosmos DB vs. OmniSci

System Properties Comparison Google Search Appliance vs. Microsoft Azure Cosmos DB vs. OmniSci

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Editorial information provided by DB-Engines

Name

Description

The Google Search Appliance consists of hardware and software for indexing documents in local networks.

Globally distributed, horizontally scalable, multi-model database service

A high performance, in-memory, column-oriented RDBMS, designed to run on GPUs

Primary database model

Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

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

Score	2.81
Rank	#90	Overall
	#10	Search engines

Score	31.43
Rank	#24	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	2.30
Rank	#104	Overall
	#50	Relational DBMS

Website

enterprise.google.com/search/products/gsa.html

azure.microsoft.com/services/cosmos-db

www.omnisci.com

Technical documentation

support.google.com/gsa

docs.microsoft.com/en-us/azure/cosmos-db

docs.omnisci.com/latest

Developer

Google

Microsoft

MapD Technologies, Inc.

Initial release

2002

2014

2016

Current release

License

Commercial or Open Source

commercial

Open Source info

Apache Version 2; enterprise edition available

Cloud-based only info

Only available as a cloud service

yes

DBaaS offerings (sponsored links) info

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++ and CUDA

Server operating systems

hosted

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

yes

XML support info

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 properties auto-indexed by default

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Administrative API
Browser interface
HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

JDBC
ODBC
Thrift

Supported programming languages

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

All languages supporting JDBC/ODBC/Thrift
Python

Server-side scripts info

Stored procedures

JavaScript

Triggers

JavaScript

Partitioning methods info

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Round robin

Replication methods info

Methods for redundantly storing data on multiple nodes

Master-slave replication

yes

Implicit feature of the cloud service

Master-master replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration info

Integration with Hadoop/HDInsight on Azure*

Consistency concepts info

Methods to ensure consistency in a distributed system

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency info

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys info

Referential integrity

Transaction concepts info

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

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency info

Support for concurrent manipulation of data

yes

Durability info

Support for making data persistent

yes

In-memory capabilities info

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

yes

User concepts info

Access control

User authentication via various security protocols

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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