DBMS > IBM Db2 warehouse vs. Kdb vs. SAP SQL Anywhere vs. SQLite vs. Weaviate

System Properties Comparison IBM Db2 warehouse vs. Kdb vs. SAP SQL Anywhere vs. SQLite vs. Weaviate

Editorial information provided by DB-Engines

Name

Description

Cloud-based data warehousing service

High performance Time Series DBMS

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Widely used embeddable, in-process RDBMS

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

Primary database model

Relational DBMS

Time Series DBMS
Vector DBMS

Relational DBMS

Vector DBMS

Secondary database models

Relational DBMS

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

Score	1.30
Rank	#164	Overall
	#75	Relational DBMS

Score	7.55
Rank	#53	Overall
	#3	Time Series DBMS
	#1	Vector DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

www.ibm.com/products/db2/warehouse

kx.com

www.sap.com/products/technology-platform/sql-anywhere.html

www.sqlite.org

github.com/weaviate/weaviate
weaviate.io

Technical documentation

code.kx.com

help.sap.com/docs/SAP_SQL_Anywhere

www.sqlite.org/docs.html

weaviate.io/developers/weaviate

Developer

IBM

Kx Systems, a division of First Derivatives plc

SAP

formerly Sybase

Dwayne Richard Hipp

Weaviate B.V.

Initial release

2014

2000

kdb was released 2000, kdb+ in 2003

1992

2000

2019

Current release

3.6, May 2018

17, July 2015

3.45.3 (15 April 2024), April 2024

1.19, May 2023

License

Commercial or Open Source

commercial

free 32-bit version

commercial

Open Source

Public Domain

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

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

Implementation language

Server operating systems

hosted

Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

server-less

Data scheme

yes

dynamic column types

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.

Import/export of XML data possible

yes

Secondary indexes

yes

table attribute 'grouped'

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 (q)

yes

SQL-92 is not fully supported

GraphQL is used as query language

APIs and other access methods

.NET Client API
JDBC
ODBC
OLE DB

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

ADO.NET
HTTP API
JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

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

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

PL/SQL, SQL PL

user defined functions

yes, in C/C++, Java, .Net or Perl

Triggers

yes

with views

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Database mirroring

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

similar paradigm used for internal processing

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

rights management via user accounts

fine grained access rights according to SQL-standard

API Keys
OpenID Connect Discovery

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
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Weaviate is an open source vector database that is robust, scalable, cloud-native,...
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Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Flexible deployment - Free, open source or fully-managed cloud vector database service...
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Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
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As a database supporting the development of generative AI and semantic search applications...
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Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
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All companies that have data.
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Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
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As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
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Licensing and pricing models

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