DBMS > Greenplum vs. SQLite vs. VelocityDB vs. Weaviate

System Properties Comparison Greenplum vs. SQLite vs. VelocityDB vs. Weaviate

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Editorial information provided by DB-Engines

Name

Description

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

Widely used embeddable, in-process RDBMS

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

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

Primary database model

Relational DBMS

Graph DBMS
Object oriented DBMS

Vector DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#15	Object oriented DBMS

Score	1.52
Rank	#153	Overall
	#6	Vector DBMS

Website

greenplum.org

www.sqlite.org

velocitydb.com

github.com/weaviate/weaviate
weaviate.io

Technical documentation

docs.greenplum.org

www.sqlite.org/docs.html

velocitydb.com/UserGuide

weaviate.io/developers/weaviate

Developer

Pivotal Software Inc.

Dwayne Richard Hipp

VelocityDB Inc

Weaviate B.V.

Initial release

2005

2000

2011

2019

Current release

7.0.0, September 2023

3.46.0 (23 May 2024), May 2024

7.x

1.19, May 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Public Domain

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

Server operating systems

Linux

server-less

Any that supports .NET

Data scheme

yes

dynamic column types

yes

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

since Version 4.2

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-92 is not fully supported

GraphQL is used as query language

APIs and other access methods

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

.Net

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

C
Java
Perl
Python
R

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

.Net

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

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

Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

via file-system locks

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

fine grained access rights according to SQL-standard

Based on Windows Authentication

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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