DBMS > FatDB vs. Google Cloud Spanner vs. ObjectBox vs. Trafodion vs. Yanza

System Properties Comparison FatDB vs. Google Cloud Spanner vs. ObjectBox vs. Trafodion vs. Yanza

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

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.

Extremely fast embedded database for small devices, IoT and Mobile

Transactional SQL-on-Hadoop DBMS

Time Series DBMS for IoT Applications

Primary database model

Document store
Key-value store

Secondary database models

Time Series DBMS

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

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Website

cloud.google.com/spanner

objectbox.io

trafodion.apache.org

yanza.com

Technical documentation

cloud.google.com/spanner/docs

docs.objectbox.io

trafodion.apache.org/documentation.html

Developer

FatCloud

Google

ObjectBox Limited

Apache Software Foundation, originally developed by HP

Yanza

Initial release

2012

2017

2014

2015

Current release

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

Open Source

Apache 2.0

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C and C++

C++, Java

Server operating systems

Windows

hosted

Android
iOS
Linux
macOS
Windows

Linux

Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

Via inetgration in SQL Server

yes

Query statements complying to ANSI 2011

yes

APIs and other access methods

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

gRPC (using protocol buffers) API
JDBC

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

Proprietary native API

ADO.NET
JDBC
ODBC

HTTP API

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

All languages supporting JDBC/ODBC/ADO.Net

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

via applications

Java Stored Procedures

Triggers

yes

via applications

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication with 3 replicas for regional instances.

online/offline synchronization between client and server

yes, via HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

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

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.

User concepts

Access control

Can implement custom security layer via applications

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

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

News

The first On-Device Vector Database: ObjectBox 4.0
16 May 2024

Edge AI: The era of on-device AI
23 April 2024

In-Memory Database Use Cases
15 February 2024

Data Viewer for Objects – announcing ObjectBox Admin
14 November 2023

Vector Databases for Edge AI
9 August 2023

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More resources

Recent citations in the news

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

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

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

Google Spanner: When Do You Need to Move to It?
11 September 2023, hackernoon.com

More AI Added to Google Cloud's Databases
28 February 2024, Datanami

provided by Google News

Evaluating HTAP Databases for Machine Learning Applications
2 November 2016, KDnuggets

HP Throws Trafodion Hat into OLTP Hadoop Ring
14 July 2014, Datanami

Low-latency, distributed database architectures are critical for emerging fog applications
7 April 2022, Embedded Computing Design

provided by Google News

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