DBMS > atoti vs. EXASOL vs. MySQL vs. PieCloudDB vs. Weaviate

System Properties Comparison atoti vs. EXASOL vs. MySQL vs. PieCloudDB vs. Weaviate

Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Widely used open source RDBMS

A cloud-native analytic database platform with new technologoy for elastic MPP

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

Primary database model

Object oriented DBMS

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Vector DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	0.32
Rank	#289	Overall
	#133	Relational DBMS

Score	1.52
Rank	#153	Overall
	#5	Vector DBMS

Website

github.com/weaviate/weaviate
weaviate.io

Technical documentation

docs.atoti.io

www.exasol.com/resources

dev.mysql.com/doc

weaviate.io/developers/weaviate

Developer

ActiveViam

Exasol

Oracle

since 2010, originally MySQL AB, then Sun

OpenPie

Weaviate B.V.

Initial release

2000

1995

2019

Current release

8.4.0, April 2024

2.1, January 2023

1.19, May 2023

License

Commercial or Open Source

commercial

free versions available

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

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

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Implementation language

Java

C and C++

Server operating systems

FreeBSD
Linux
OS X
Solaris
Windows

hosted

Data scheme

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.

yes

Secondary indexes

yes

all data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

with proprietary extensions

yes

GraphQL is used as query language

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

ADO.NET
JDBC
ODBC
Proprietary native API

CLI Client
JDBC
ODBC

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

Java
Lua
Python
R

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Java
PL/SQL
Python
R

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

Python

user defined functions

yes

proprietary syntax

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

table locks or row locks depending on storage engine

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, groups and roles according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

User Roles and pluggable authentication with full SQL Standard

API Keys
OpenID Connect Discovery

More information provided by the system vendor

Specific characteristics

PieCloudDB, OpenPie's flagship product, is a cutting-edge cloud-native data warehouse....
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Weaviate is an open source vector database that is robust, scalable, cloud-native,...
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Competitive advantages

Extreme Elastic: PieCloudDB utilizes a cutting-edge eMPP cloud-native architecture...
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Flexible deployment - Free, open source or fully-managed cloud vector database service...
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Typical application scenarios

PieCloudDB is ideal for Data mining applications that require extreme scalability...
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As a database supporting the development of generative AI and semantic search applications...
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Key customers

Sail-Cloud China Shipbuilding Group Haizhou System Soochow Securities etc.,
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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

PieCloudDB Community Edition: Community License, Free Download, Self-Hosted Deployment；...
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Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.