DBMS > Firebase Realtime Database vs. Machbase Neo vs. searchxml vs. SwayDB vs. XTDB

System Properties Comparison Firebase Realtime Database vs. Machbase Neo vs. searchxml vs. SwayDB vs. XTDB

Editorial information provided by DB-Engines

Name

Description

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

TimeSeries DBMS for AIoT and BigData

DBMS for structured and unstructured content wrapped with an application server

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

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

Primary database model

Document store

Time Series DBMS

Native XML DBMS
Search engine

Key-value store

Document store

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

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

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

firebase.google.com/products/realtime-database

machbase.com

www.searchxml.net/category/products

swaydb.simer.au

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

Technical documentation

firebase.google.com/docs/database

machbase.com/dbms

www.searchxml.net/support/handouts

www.xtdb.com/docs

Developer

Google

acquired by Google 2014

Machbase

informationpartners gmbh

Simer Plaha

Juxt Ltd.

Initial release

2012

2013

2015

2018

2019

Current release

V8.0, August 2023

1.0

1.19, September 2021

License

Commercial or Open Source

commercial

free test version available

commercial

Open Source

GNU Affero GPL V3.0

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Scala

Clojure

Server operating systems

hosted

Linux
macOS
Windows

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

limited SQL, making use of Apache Calcite

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

RESTful HTTP API
WebDAV
XQuery
XSLT

HTTP REST
JDBC

Supported programming languages

Java
JavaScript
Objective-C

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

C++

most other programming languages supported via APIs

Java
Kotlin
Scala

Clojure
Java

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

on the application server

Triggers

Callbacks are triggered when data changes

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

yes

sychronisation to multiple collections

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

multiple readers, single writer

Atomic execution of operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

volatile and lookup table

yes

User concepts

Access control

yes, based on authentication and database rules

simple password-based access control

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

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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