DBMS > BigObject vs. FatDB vs. Google Cloud Spanner vs. Machbase Neo

System Properties Comparison BigObject vs. FatDB vs. Google Cloud Spanner vs. Machbase Neo

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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.

Description

Analytic DBMS for real-time computations and queries

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.

TimeSeries DBMS for AIoT and BigData

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Document store
Key-value store

Relational DBMS

Time Series DBMS

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Website

bigobject.io

cloud.google.com/spanner

machbase.com

Technical documentation

docs.bigobject.io

cloud.google.com/spanner/docs

machbase.com/dbms

Developer

BigObject, Inc.

FatCloud

Google

Machbase

Initial release

2015

2012

2017

2013

Current release

V8.0, August 2023

License

Commercial or Open Source

commercial

free community edition available

commercial

free test version available

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

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Windows

hosted

Linux
macOS
Windows

Data scheme

yes

schema-free

yes

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

SQL-like DML and DDL statements

Via inetgration in SQL Server

yes

Query statements complying to ANSI 2011

SQL-like query language

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

.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

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Server-side scripts

Stored procedures

Lua

yes

via applications

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

Multi-source replication with 3 replicas for regional instances.

selectable replication factor

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

none

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

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

Transaction concepts

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

ACID

Strict serializable isolation

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

volatile and lookup table

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)

simple password-based access control

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

Google Cloud Spanner Is Now Half the Cost of Amazon DynamoDB
13 October 2023, Datanami

provided by Google News

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