DBMS > Apache Hive vs. Dolt vs. FatDB vs. LMDB

System Properties Comparison Apache Hive vs. Dolt vs. FatDB vs. LMDB

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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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

A MySQL compatible DBMS with Git-like versioning of data and schema

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

A high performant, light-weight, embedded key-value database library

Primary database model

Relational DBMS

Document store
Key-value store

Key-value store

Secondary database models

Document store

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

Score	75.77
Rank	#16	Overall
	#11	Relational DBMS

Score	0.60
Rank	#232	Overall
	#106	Relational DBMS

Score	1.75
Rank	#129	Overall
	#20	Key-value stores

Website

hive.apache.org

github.com/dolthub/dolt
www.dolthub.com

www.symas.com/symas-embedded-database-lmdb

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

docs.dolthub.com

www.lmdb.tech/doc

Developer

Apache Software Foundation

initially developed by Facebook

DoltHub Inc

FatCloud

Symas

Initial release

2012

2018

2012

2011

Current release

3.1.3, April 2022

0.9.32, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

commercial

Open Source

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

Java

Server operating systems

All OS with a Java VM

Linux
macOS
Windows

Windows

Linux
Unix
Windows

Data scheme

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

SQL-like DML and DDL statements

yes

Via inetgration in SQL Server

APIs and other access methods

JDBC
ODBC
Thrift

CLI Client
HTTP REST

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

Supported programming languages

C++
Java
PHP
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

currently in alpha release

yes

via applications

Triggers

yes

via applications

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

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

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

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users, groups and roles

Only one user is configurable, and must be specified in the config file at startup

Can implement custom security layer via applications

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