DBMS > Drizzle vs. IBM Db2 Event Store vs. Newts vs. Qdrant

System Properties Comparison Drizzle vs. IBM Db2 Event Store vs. Newts vs. Qdrant

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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.

Distributed Event Store optimized for Internet of Things use cases

Time Series DBMS based on Cassandra

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

Primary database model

Relational DBMS

Event Store
Time Series DBMS

Time Series DBMS

Vector DBMS

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

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	1.28
Rank	#167	Overall
	#6	Vector DBMS

Website

www.ibm.com/products/db2-event-store

opennms.github.io/newts

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

www.ibm.com/docs/en/db2-event-store

github.com/OpenNMS/newts/wiki

qdrant.tech/documentation

Developer

Drizzle project, originally started by Brian Aker

IBM

OpenNMS Group

Qdrant

Initial release

2008

2017

2014

2021

Current release

7.2.4, September 2012

2.0

License

Commercial or Open Source

Open Source

GNU GPL

commercial

free developer edition available

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

C and C++

Java

Rust

Server operating systems

FreeBSD
Linux
OS X

Linux

Linux, macOS, Windows for the developer addition

Linux
OS X
Windows

Docker
Linux
macOS
Windows

Data scheme

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.

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

yes

with proprietary extensions

yes

through the embedded Spark runtime

APIs and other access methods

JDBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

HTTP REST
Java API

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

C
C++
Java
PHP

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

Java

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

Server-side scripts

Stored procedures

yes

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Active-active shard replication

selectable replication factor

based on Cassandra

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

based on Cassandra
Immediate Consistency

based on Cassandra

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

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

Key-based authentication

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More resources

DB-Engines blog posts

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1 April 2015, Paul Andlinger

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