DBMS > Badger vs. Brytlyt vs. Geode vs. GeoMesa

System Properties Comparison Badger vs. Brytlyt vs. Geode vs. GeoMesa

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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.

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

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

Primary database model

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Website

github.com/dgraph-io/badger

brytlyt.io

geode.apache.org

www.geomesa.org

Technical documentation

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

docs.brytlyt.io

geode.apache.org/docs

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

Developer

DGraph Labs

Brytlyt

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

CCRi and others

Initial release

2017

2016

2002

2014

Current release

5.0, August 2023

1.1, February 2017

4.0.5, February 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Apache License 2.0

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++ and CUDA

Java

Scala

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

All OS with a Java VM

the JDK (8 or later) is also required

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.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (OQL)

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Java Client API
Memcached protocol
RESTful HTTP API

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

.Net
All JVM based languages
C++
Groovy
Java
Scala

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

user defined functions

Triggers

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

depending on storage layer

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

Multi-source replication

depending on storage layer

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

depending on storage layer

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes, on a single node

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

depending on storage layer

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights per client and object definable

yes

depending on the DBMS used for storage

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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Recent citations in the news

Brytlyt releases version 5.0, introducing a more intuitive, intelligent and flexible analytics platform
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London’s Brytlyt raises €4.4 million for its data analytics and visualisation technology
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