DBMS > Badger vs. GeoMesa vs. Linter vs. Lovefield

System Properties Comparison Badger vs. GeoMesa vs. Linter vs. Lovefield

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Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

RDBMS for high security requirements

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Key-value store

Spatial DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Website

github.com/dgraph-io/badger

www.geomesa.org

linter.ru

google.github.io/lovefield

Technical documentation

godoc.org/github.com/dgraph-io/badger

www.geomesa.org/documentation/stable/user/index.html

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

Developer

DGraph Labs

CCRi and others

relex.ru

Google

Initial release

2017

2014

1990

2014

Current release

5.0.0, May 2024

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache License 2.0

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Scala

C and C++

JavaScript

Server operating systems

BSD
Linux
OS X
Solaris
Windows

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

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

tested with Chrome, Firefox, IE, Safari

Data scheme

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

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Supported programming languages

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

JavaScript

Server-side scripts

Stored procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

depending on storage layer

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

depending on storage layer

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

depending on storage layer

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

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

In-memory capabilities

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

depending on storage layer

yes

using MemoryDB

User concepts

Access control

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard

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