DBMS > BoltDB vs. Firebase Realtime Database vs. RisingWave vs. RocksDB vs. Weaviate

System Properties Comparison BoltDB vs. Firebase Realtime Database vs. RisingWave vs. RocksDB vs. Weaviate

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.

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

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

Primary database model

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

Score	0.80
Rank	#215	Overall
	#31	Key-value stores

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	0.64
Rank	#238	Overall
	#110	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	1.52
Rank	#153	Overall
	#5	Vector DBMS

Website

github.com/boltdb/bolt

firebase.google.com/products/realtime-database

www.risingwave.com/database

rocksdb.org

github.com/weaviate/weaviate
weaviate.io

Technical documentation

firebase.google.com/docs/database

docs.risingwave.com/docs/current/intro

github.com/facebook/rocksdb/wiki

weaviate.io/developers/weaviate

Developer

Google

acquired by Google 2014

RisingWave Labs

Facebook, Inc.

Weaviate B.V.

Initial release

2013

2012

2022

2013

2019

Current release

1.2, September 2023

9.2.1, May 2024

1.19, May 2023

License

Commercial or Open Source

Open Source

MIT License

commercial

Open Source

Apache Version 2.0

Open Source

BSD

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

Rust

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

hosted

Docker
Linux
macOS

Linux

Data scheme

schema-free

yes

schema-free

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

Standard SQL-types and JSON

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.

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

GraphQL is used as query language

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
PostgreSQL wire protocol

C++ API
Java API

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

Java
JavaScript
Objective-C

Go
Java
JavaScript (Node.js)
Python

C
C++
Go
Java
Perl
Python
Ruby

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

limited functionality with using 'rules'

UDFs in Python or Java

Triggers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

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

User concepts

Access control

yes, based on authentication and database rules

Users and Roles

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,...
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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.
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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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