DBMS > Apache Phoenix vs. DataFS vs. EsgynDB vs. Realm vs. Weaviate

System Properties Comparison Apache Phoenix vs. DataFS vs. EsgynDB vs. Realm vs. Weaviate

Editorial information provided by DB-Engines

Name

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

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

Primary database model

Secondary database models

Graph DBMS

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

github.com/weaviate/weaviate
weaviate.io

Technical documentation

phoenix.apache.org

dev.mobiland.com/Overview.xsp

realm.io/docs

weaviate.io/developers/weaviate

Developer

Apache Software Foundation

Mobiland AG

Esgyn

Realm, acquired by MongoDB in May 2019

Weaviate B.V.

Initial release

2014

2018

2015

2014

2019

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

1.1.263, October 2022

1.19, May 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

commercial license available with Weaviate Enterprise

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

Java

C++, Java

Server operating systems

Linux
Unix
Windows

Windows

Linux

Android
Backend: server-less
iOS
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

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

JDBC

.NET Client API
Proprietary client DLL
WinRT client

ADO.NET
JDBC
ODBC

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

.Net
C
C#
C++
VB.Net

All languages supporting JDBC/ODBC/ADO.Net

.Net
Java

with Android only
Objective-C
React Native
Swift

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

runs within the applications so server-side scripts are unnecessary

Triggers

no, except callback-events from server when changes happened

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

Proprietary Sharding system

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication between multi datacenters

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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.

yes

In-Memory realm

yes

User concepts

Access control

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Windows-Profile

fine grained access rights according to SQL-standard

yes

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...
» more

Typical application scenarios

As a database supporting the development of generative AI and semantic search applications...
» more

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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We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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Recent citations in the news

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services
2 June 2016, AWS Blog

Azure #HDInsight Apache Phoenix now supports Zeppelin
16 August 2018, azure.microsoft.com

Bridge the SQL-NoSQL gap with Apache Phoenix
4 February 2016, InfoWorld

Apache Calcite, FreeMarker, Gora, Phoenix, and Solr updated
27 March 2017, SDTimes.com

Hortonworks Starts Hadoop Summit with Data Platform Update -- ADTmag
28 June 2016, ADT Magazine

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12 September 2017, Solutions Review

Kotlin Programming Language Will Surpass Java On Android Next Year
15 October 2017, Fossbytes

Java Synthetic Methods — What are these? | by Vaibhav Singh
27 February 2021, DataDrivenInvestor

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