DBMS > Google Cloud Bigtable vs. Microsoft Azure Table Storage vs. SAP HANA vs. Snowflake vs. UniData,UniVerse

System Properties Comparison Google Cloud Bigtable vs. Microsoft Azure Table Storage vs. SAP HANA vs. Snowflake vs. UniData,UniVerse

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.

A Wide Column Store for rapid development using massive semi-structured datasets

In-memory, column based data store. Available as appliance or cloud service

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

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Key-value store
Wide column store

Wide column store

Relational DBMS

Multivalue DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	3.16
Rank	#97	Overall
	#2	Multivalue DBMS

Website

cloud.google.com/bigtable

azure.microsoft.com/en-us/services/storage/tables

www.sap.com/products/hana.html

www.snowflake.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

cloud.google.com/bigtable/docs

help.sap.com/hana

docs.snowflake.net/manuals/index.html

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Google

Microsoft

SAP

Snowflake Computing Inc.

Rocket Software

Initial release

2015

2012

2010

2014

1985

Current release

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Server operating systems

hosted

Appliance or cloud-service

hosted

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

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

schema-free

Typing

predefined data types such as float or date

yes

optional

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

yes

APIs and other access methods

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

RESTful HTTP API

JDBC
ODBC

CLI Client
JDBC
ODBC

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

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

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

JavaScript (Node.js)
Python

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

SQLScript, R

user defined functions

yes

Triggers

yes

similar concept for controling cloud resources

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

yes

none

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. Replication either local, cross-facility or geo-redundant.

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

optimistic locking

ACID

configurable

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

User concepts

Access control

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

Access rights based on private key authentication or shared access signatures

yes

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

Access rights according to SQL-standard and operating system based

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