DBMS > FatDB vs. Google BigQuery vs. IBM Cloudant vs. Immudb vs. Kinetica

System Properties Comparison FatDB vs. Google BigQuery vs. IBM Cloudant vs. Immudb vs. Kinetica

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.

Large scale data warehouse service with append-only tables

Database as a Service offering based on Apache CouchDB

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

Fully vectorized database across both GPUs and CPUs

Primary database model

Document store
Key-value store

Secondary database models

Relational DBMS

Spatial DBMS
Time Series DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	0.31
Rank	#295	Overall
	#42	Key-value stores

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Website

cloud.google.com/bigquery

www.ibm.com/products/cloudant

github.com/codenotary/immudb
immudb.io

www.kinetica.com

Technical documentation

cloud.google.com/bigquery/docs

cloud.ibm.com/docs/Cloudant

docs.immudb.io

docs.kinetica.com

Developer

FatCloud

Google

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Codenotary

Kinetica

Initial release

2012

2010

2020

2012

Current release

1.2.3, April 2022

7.1, August 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

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

Erlang

C, C++

Server operating systems

Windows

hosted

BSD
Linux
macOS
Solaris
Windows
z/OS

Linux

Data scheme

schema-free

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

Via inetgration in SQL Server

yes

SQL-like syntax

SQL-like DML and DDL statements

APIs and other access methods

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

RESTful HTTP/JSON API

gRPC protocol
PostgreSQL wire protocol

JDBC
ODBC
RESTful HTTP API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
Java
JavaScript
Objective-C
PHP
Ruby

.Net
Go
Java
JavaScript (Node.js)
Python

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

via applications

user defined functions

in JavaScript

View functions (Map-Reduce) in JavaScript

user defined functions

Triggers

yes

via applications

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

Source-replica replication

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

Eventual Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

Since BigQuery is designed for querying data

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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

GPU vRAM or System RAM

User concepts

Access control

Can implement custom security layer via applications

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights for users can be defined per database

Access rights for users and roles on table level

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