DBMS > Amazon DynamoDB vs. Databend vs. EsgynDB vs. Firebase Realtime Database vs. Weaviate

System Properties Comparison Amazon DynamoDB vs. Databend vs. EsgynDB vs. Firebase Realtime Database vs. Weaviate

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

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

Primary database model

Document store
Key-value store

Relational DBMS

Document store

Vector DBMS

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	1.52
Rank	#153	Overall
	#5	Vector DBMS

Website

aws.amazon.com/dynamodb

github.com/datafuselabs/databend
www.databend.com

www.esgyn.cn

firebase.google.com/products/realtime-database

github.com/weaviate/weaviate
weaviate.io

Technical documentation

docs.aws.amazon.com/dynamodb

docs.databend.com

firebase.google.com/docs/database

weaviate.io/developers/weaviate

Developer

Amazon

Databend Labs

Esgyn

Google

acquired by Google 2014

Weaviate B.V.

Initial release

2012

2021

2015

2012

2019

Current release

1.0.59, April 2023

1.19, May 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2.0

commercial

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++, Java

Server operating systems

hosted

hosted
Linux
macOS

Linux

hosted

Data scheme

schema-free

yes

schema-free

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

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

RESTful HTTP API

CLI Client
JDBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

Android
iOS
JavaScript API
RESTful HTTP API

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python
Rust

All languages supporting JDBC/ODBC/ADO.Net

Java
JavaScript
Objective-C

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

Java Stored Procedures

limited functionality with using 'rules'

Triggers

yes

by integration with AWS Lambda

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication between multi datacenters

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

yes

ACID

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Users with fine-grained authorization concept, user roles

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

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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