DBMS > Google Cloud Bigtable vs. Microsoft Azure AI Search vs. Sadas Engine vs. SiriDB vs. Transbase

System Properties Comparison Google Cloud Bigtable vs. Microsoft Azure AI Search vs. Sadas Engine vs. SiriDB vs. Transbase

Editorial information provided by DB-Engines

Name

Description

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Search-as-a-service for web and mobile app development

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Open Source Time Series DBMS

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Key-value store
Wide column store

Secondary database models

Vector DBMS

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

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

cloud.google.com/bigtable

azure.microsoft.com/en-us/services/search

www.sadasengine.com

siridb.com

www.transaction.de/en/products/transbase.html

Technical documentation

cloud.google.com/bigtable/docs

learn.microsoft.com/en-us/azure/search

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.siridb.com

www.transaction.de/en/products/transbase/features.html

Developer

Google

Microsoft

SADAS s.r.l.

Cesbit

Transaction Software GmbH

Initial release

2015

2006

2017

1987

Current release

8.0

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

free trial version available

Open Source

MIT License

commercial

free development license

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

C++

C and C++

Server operating systems

hosted

AIX
Linux
Windows

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

RESTful HTTP API

JDBC
ODBC
Proprietary protocol

HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

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

C#
Java
JavaScript
Python

.Net
C
C#
C++
Groovy
Java
PHP
Python

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Internal replication in Colossus, and regional replication between two clusters in different zones

yes

Implicit feature of the cloud service

none

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

yes

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

managed by 'Learn by Usage'

yes

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

yes

using Azure authentication

Access rights for users, groups and roles according to SQL-standard

simple rights management via user accounts

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

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Google Cloud makes it cheaper to run smaller workloads on Bigtable
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Google introduces Cloud Bigtable managed NoSQL database to process data at scale
6 May 2015, VentureBeat

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