DBMS > Apache Phoenix vs. Machbase Neo vs. SAP HANA vs. Weaviate

System Properties Comparison Apache Phoenix vs. Machbase Neo vs. SAP HANA vs. Weaviate

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Editorial information provided by DB-Engines

Name

Description

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

TimeSeries DBMS for AIoT and BigData

In-memory, column based data store. Available as appliance or cloud service

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

Primary database model

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.90
Rank	#125	Overall
	#59	Relational DBMS

Score	0.07
Rank	#348	Overall
	#34	Time Series DBMS

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Score	1.48
Rank	#149	Overall
	#8	Vector DBMS

Website

phoenix.apache.org

machbase.com

www.sap.com/products/hana.html

github.com/weaviate/weaviate
weaviate.io

Technical documentation

phoenix.apache.org

machbase.com/dbms

help.sap.com/hana

weaviate.io/developers/weaviate

Developer

Apache Software Foundation

Machbase

SAP

Weaviate B.V.

Initial release

2014

2013

2010

2019

Current release

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

V8.0, August 2023

2.0 SPS07 (April 4, 2023), April 2023

1.19, May 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free test version available

commercial

Open Source

commercial license available with Weaviate Enterprise

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Server operating systems

Linux
Unix
Windows

Linux
macOS
Windows

Appliance or cloud-service

Data scheme

yes

late-bound, schema-on-read capabilities

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

SQL-like query language

yes

GraphQL is used as query language

APIs and other access methods

JDBC

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

JDBC
ODBC

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

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

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

user defined functions

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

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

volatile and lookup table

yes

User concepts

Access control

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

simple password-based access control

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,...
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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.
» 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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