DBMS > atoti vs. Kdb vs. Microsoft Azure Data Explorer vs. MySQL vs. Weaviate

System Properties Comparison atoti vs. Kdb vs. Microsoft Azure Data Explorer vs. MySQL 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 Time Series DBMS

Fully managed big data interactive analytics platform

Widely used open source RDBMS

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

Primary database model

Object oriented DBMS

Time Series DBMS
Vector DBMS

Relational DBMS

column oriented

Relational DBMS

Key/Value like access via memcached API

Vector DBMS

Secondary database models

Relational DBMS

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

Document store
Spatial DBMS

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

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

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

atoti.io

kx.com

azure.microsoft.com/services/data-explorer

www.mysql.com

github.com/weaviate/weaviate
weaviate.io

Technical documentation

docs.atoti.io

code.kx.com

docs.microsoft.com/en-us/azure/data-explorer

dev.mysql.com/doc

weaviate.io/developers/weaviate

Developer

ActiveViam

Kx Systems, a division of First Derivatives plc

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Weaviate B.V.

Initial release

2000

kdb was released 2000, kdb+ in 2003

2019

1995

2019

Current release

3.6, May 2018

cloud service with continuous releases

8.4.0, April 2024

1.19, May 2023

License

Commercial or Open Source

commercial

free versions available

commercial

free 32-bit version

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

Java

C and C++

Server operating systems

Linux
OS X
Solaris
Windows

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

Fixed schema with schema-less datatypes (dynamic)

yes

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types

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

table attribute 'grouped'

all fields are automatically indexed

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)

SQL-like query language (q)

Kusto Query Language (KQL), SQL subset

yes

with proprietary extensions

GraphQL is used as query language

APIs and other access methods

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

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

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

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

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

Python

user defined functions

Yes, possible languages: KQL, Python, R

yes

proprietary syntax

Triggers

yes

with views

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

horizontal partitioning

Sharding

Implicit feature of the cloud service

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

similar paradigm used for internal processing

Spark connector (open source): github.com/Azure/azure-kusto-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

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

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

rights management via user accounts

Azure Active Directory Authentication

Users with fine-grained authorization concept

no user groups or roles

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