DBMS > Google Cloud Spanner vs. jBASE vs. Microsoft Azure Table Storage vs. Sadas Engine vs. SiriDB

System Properties Comparison Google Cloud Spanner vs. jBASE vs. Microsoft Azure Table Storage vs. Sadas Engine vs. SiriDB

Editorial information provided by DB-Engines

Name

Description

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

A robust multi-value DBMS comprising development tools and middleware

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

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

Open Source Time Series DBMS

Primary database model

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

Score	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	1.49
Rank	#156	Overall
	#3	Multivalue DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Website

cloud.google.com/spanner

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

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

www.sadasengine.com

siridb.com

Technical documentation

cloud.google.com/spanner/docs

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

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

docs.siridb.com

Developer

Google

Rocket Software (formerly Zumasys)

Microsoft

SADAS s.r.l.

Cesbit

Initial release

2017

1991

2012

2006

2017

Current release

5.7

8.0

License

Commercial or Open Source

commercial

free trial version available

Open Source

MIT 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++

Server operating systems

hosted

AIX
Linux
Windows

hosted

AIX
Linux
Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

optional

yes

Numeric data

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

Query statements complying to ANSI 2011

Embedded SQL for jBASE in BASIC

yes

APIs and other access methods

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

RESTful HTTP API

JDBC
ODBC
Proprietary protocol

HTTP API

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

.Net
Basic
Jabbascript
Java

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

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

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

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

Multi-source replication with 3 replicas for regional instances.

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

ACID

Strict serializable isolation

ACID

optimistic locking

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)

Access rights can be defined down to the item level

Access rights based on private key authentication or shared access signatures

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

simple rights management via user accounts

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More resources

Recent citations in the news

Google's Cloud Spanner Now Spans Continents … Like It's Supposed to Do
31 May 2024, Data Center Knowledge

Google Improves Cloud Spanner: More Compute and Storage without Price Increase
14 October 2023, InfoQ.com

Google turns up the heat on AWS, claims Cloud Spanner is half the cost of DynamoDB
11 October 2023, TechCrunch

Google makes its Cloud Spanner database service faster and more cost-efficient
11 October 2023, SiliconANGLE News

Google Cloud just fired a major volley at AWS as the cloud wars heat up
12 October 2023, TechRadar

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Inside Azure File Storage
7 October 2015, azure.microsoft.com

How to write data to Azure Table Store with an Azure Function
14 April 2017, Experts Exchange

provided by Google News

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