DBMS > Badger vs. GeoMesa vs. NSDb vs. searchxml

System Properties Comparison Badger vs. GeoMesa vs. NSDb vs. searchxml

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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.

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Key-value store

Spatial DBMS

Time Series DBMS

Native XML DBMS
Search engine

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

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

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

github.com/dgraph-io/badger

www.geomesa.org

nsdb.io

www.searchxml.net/category/products

Technical documentation

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

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

nsdb.io/Architecture

www.searchxml.net/support/handouts

Developer

DGraph Labs

CCRi and others

informationpartners gmbh

Initial release

2017

2014

2017

2015

Current release

4.0.5, February 2024

1.0

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache License 2.0

Open Source

Apache Version 2.0

commercial

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

Scala

Java, Scala

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
macOS

Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

gRPC
HTTP REST
WebSocket

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

Java
Scala

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

yes

on the application server

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

depending on storage layer

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

depending on storage layer

yes

sychronisation to multiple collections

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

In-memory capabilities

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

depending on storage layer

User concepts

Access control

yes

depending on the DBMS used for storage

Domain, group and role-based access control at the document level and for application services

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