DBMS > FatDB vs. Google Cloud Bigtable vs. Lovefield vs. YottaDB

System Properties Comparison FatDB vs. Google Cloud Bigtable vs. Lovefield vs. YottaDB

Please select another system to include it in the comparison.

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

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

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

Embeddable relational database for web apps written in pure JavaScript

A fast and solid embedded Key-value store

Primary database model

Document store
Key-value store

Key-value store
Wide column store

Relational DBMS

Key-value store

Secondary database models

Relational DBMS

using the Octo plugin

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	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

cloud.google.com/bigtable

google.github.io/lovefield

yottadb.com

Technical documentation

cloud.google.com/bigtable/docs

github.com/google/lovefield/blob/master/docs/spec_index.md

yottadb.com/resources/documentation

Developer

FatCloud

Google

YottaDB, LLC

Initial release

2012

2015

2014

2001

Current release

2.1.12, February 2017

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

AGPL 3.0

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

JavaScript

Server operating systems

Windows

hosted

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Docker
Linux

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

SQL-like query language

via JavaScript builder pattern

by using the Octo plugin

APIs and other access methods

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

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

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

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

JavaScript

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes

via applications

Triggers

yes

via applications

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

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

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes

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)

Users and groups based on OS-security mechanisms

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

Google Cloud makes it cheaper to run smaller workloads on Bigtable
7 April 2020, TechCrunch

Google introduces Cloud Bigtable managed NoSQL database to process data at scale
6 May 2015, VentureBeat

provided by Google News

Share this page