DBMS > Apache Kylin vs. STSdb vs. Vertica vs. Weaviate

System Properties Comparison Apache Kylin vs. STSdb vs. Vertica vs. Weaviate

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Editorial information provided by DB-Engines

Name

Description

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

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

Primary database model

Column oriented

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	1.14
Rank	#171	Overall
	#77	Relational DBMS

Score	0.03
Rank	#365	Overall
	#54	Key-value stores

Score	9.62
Rank	#42	Overall
	#26	Relational DBMS

Score	1.48
Rank	#149	Overall
	#8	Vector DBMS

Website

kylin.apache.org

github.com/STSSoft/STSdb4

www.vertica.com

github.com/weaviate/weaviate
weaviate.io

Technical documentation

kylin.apache.org/docs

vertica.com/documentation

weaviate.io/developers/weaviate

Developer

Apache Software Foundation, originally contributed from eBay Inc

STS Soft SC

OpenText

previously Micro Focus and Hewlett Packard

Weaviate B.V.

Initial release

2015

2011

2005

2019

Current release

3.1.0, July 2020

4.0.8, September 2015

12.0.3, January 2023

1.19, May 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GPLv2, commercial license available

commercial

Limited community edition free

Open Source

commercial license available with Weaviate Enterprise

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

Server operating systems

Linux

Windows

Linux

Data scheme

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

yes

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

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

GraphQL is used as query language

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

.NET Client API

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

C#
Java

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning, hierarchical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Bi-directional Spark integration

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

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; supports Kerberos, LDAP, Ident and hash

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...
» more

Licensing and pricing models

Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

Weaviate, an ANN Database with CRUD support
2 February 2021, Etienne Dilocker, SeMI Technologies (sponsor)

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Recent citations in the news

Overhauling Apache Kylin for the cloud
18 November 2021, InfoWorld

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9 December 2015, eBay Inc.

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10 August 2021, Blocks & Files

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