DBMS > Apache Pinot vs. Blueflood vs. Drizzle vs. RavenDB

System Properties Comparison Apache Pinot vs. Blueflood vs. Drizzle vs. RavenDB

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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

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

Scalable TimeSeries DBMS based on Cassandra

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

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.38
Rank	#275	Overall
	#126	Relational DBMS

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Website

pinot.apache.org

blueflood.io

ravendb.net

Technical documentation

docs.pinot.apache.org

github.com/rax-maas/blueflood/wiki

ravendb.net/docs

Developer

Apache Software Foundation and contributors

Rackspace

Drizzle project, originally started by Brian Aker

Hibernating Rhinos

Initial release

2015

2013

2008

2010

Current release

1.0.0, September 2023

7.2.4, September 2012

5.4, July 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

GNU GPL

Open Source

AGPL version 3, commercial license available

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

Java

C++

Server operating systems

All OS with a Java JDK11 or higher

Linux
OS X

FreeBSD
Linux
OS X

Linux
macOS
Raspberry Pi
Windows

Data scheme

yes

predefined scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

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

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

SQL-like query language (RQL)

APIs and other access methods

JDBC

HTTP REST

JDBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

Go
Java
Python

C
C++
Java
PHP

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

ACID, Cluster-wide transaction available

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.

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Authorization levels configured per client per database

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

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