DBMS > Drizzle vs. Heroic vs. Kinetica vs. Microsoft SQL Server vs. Qdrant

System Properties Comparison Drizzle vs. Heroic vs. Kinetica vs. Microsoft SQL Server vs. Qdrant

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Fully vectorized database across both GPUs and CPUs

Microsofts flagship relational DBMS

A high-performance vector database with neural network or semantic-based matching

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	0.42
Rank	#261	Overall
	#120	Relational DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	1.53
Rank	#145	Overall
	#7	Vector DBMS

Website

github.com/spotify/heroic

www.kinetica.com

www.microsoft.com/en-us/sql-server

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

spotify.github.io/heroic

docs.kinetica.com

learn.microsoft.com/en-US/sql/sql-server

qdrant.tech/documentation

Developer

Drizzle project, originally started by Brian Aker

Spotify

Kinetica

Microsoft

Qdrant

Initial release

2008

2014

2012

1989

2021

Current release

7.2.4, September 2012

7.1, August 2021

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

C, C++

C++

Rust

Server operating systems

FreeBSD
Linux
OS X

Linux

Linux
Windows

Docker
Linux
macOS
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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

via Elasticsearch

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

yes

with proprietary extensions

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

C
C++
Java
PHP

C++
Java
JavaScript (Node.js)
Python

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

user defined functions

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

hooks for callbacks inside the server can be used.

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Source-replica replication

yes, but depending on the SQL-Server Edition

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency, tunable 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

GPU vRAM or System RAM

yes

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

Key-based authentication

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