DBMS > Firebase Realtime Database vs. GeoMesa vs. TimescaleDB vs. Weaviate

System Properties Comparison Firebase Realtime Database vs. GeoMesa vs. TimescaleDB vs. Weaviate

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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.

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

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

An AI-native realtime vector database engine that integrates scalable machine learning models.

Primary database model

Secondary database models

Relational DBMS

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

Score	13.60
Rank	#39	Overall
	#6	Document stores

Score	0.78
Rank	#214	Overall
	#4	Spatial DBMS

Score	4.06
Rank	#73	Overall
	#5	Time Series DBMS

Score	1.48
Rank	#149	Overall
	#8	Vector DBMS

Website

firebase.google.com/products/realtime-database

www.geomesa.org

www.timescale.com

github.com/weaviate/weaviate
weaviate.io

Technical documentation

firebase.google.com/docs/database

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

docs.timescale.com

weaviate.io/developers/weaviate

Developer

Google

acquired by Google 2014

CCRi and others

Timescale

Weaviate B.V.

Initial release

2012

2014

2017

2019

Current release

5.0.1, July 2024

2.15.0, May 2024

1.19, May 2023

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

Open Source

Apache 2.0

Open Source

commercial license available with Weaviate Enterprise

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

Scala

Server operating systems

hosted

Linux
OS X
Windows

Data scheme

schema-free

yes

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

yes

string, int, float, geo point, date, cross reference, fuzzy references

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 data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed

SQL

Support of SQL

yes

full PostgreSQL SQL syntax

GraphQL is used as query language

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

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

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

Java
JavaScript
Objective-C

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

limited functionality with using 'rules'

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

yes, across time and space (hash partitioning) attributes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

Source-replica replication with hot standby and reads on replicas

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

depending on storage layer

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

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.

depending on storage layer

yes

User concepts

Access control

yes, based on authentication and database rules

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard

API Keys
OpenID Connect Discovery

More information provided by the system vendor

Specific characteristics

Weaviate is an open source vector database that is robust, scalable, cloud-native,...
» more

Competitive advantages

Flexible deployment - Free, open source or fully-managed cloud vector database service...
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Typical application scenarios

As a database supporting the development of generative AI and semantic search applications...
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Key customers

All companies that have data.
» more

Market metrics

As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
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Licensing and pricing models

Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and 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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Spatial database management systems
6 April 2021, Matthias Gelbmann

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Weaviate, an ANN Database with CRUD support
2 February 2021, Etienne Dilocker, SeMI Technologies (sponsor)

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Recent citations in the news

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