DBMS > FatDB vs. Kinetica vs. LevelDB vs. XTDB

System Properties Comparison FatDB vs. Kinetica vs. LevelDB vs. XTDB

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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

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

Fully vectorized database across both GPUs and CPUs

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Document store
Key-value store

Relational DBMS

Key-value store

Document store

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.kinetica.com

github.com/google/leveldb

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.kinetica.com

github.com/google/leveldb/blob/main/doc/index.md

www.xtdb.com/docs

Developer

FatCloud

Kinetica

Google

Juxt Ltd.

Initial release

2012

2011

2019

Current release

7.1, August 2021

1.23, February 2021

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C, C++

C++

Clojure

Server operating systems

Windows

Linux

Illumos
Linux
OS X
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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 DML and DDL statements

limited SQL, making use of Apache Calcite

APIs and other access methods

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

JDBC
ODBC
RESTful HTTP API

HTTP REST
JDBC

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Clojure
Java

Server-side scripts

Stored procedures

yes

via applications

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

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

none

yes, each node contains all data

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 or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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 rights for users and roles on table level

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