DBMS > Apache Pinot vs. Blueflood vs. FeatureBase vs. TDSQL for MySQL

System Properties Comparison Apache Pinot vs. Blueflood vs. FeatureBase vs. TDSQL for MySQL

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Editorial information provided by DB-Engines

Name

Description

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

Scalable TimeSeries DBMS based on Cassandra

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.40
Rank	#270	Overall
	#125	Relational DBMS

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	0.22
Rank	#309	Overall
	#139	Relational DBMS

Score	0.85
Rank	#205	Overall
	#95	Relational DBMS

Website

pinot.apache.org

blueflood.io

www.featurebase.com

www.tencentcloud.com/products/dcdb

Technical documentation

docs.pinot.apache.org

github.com/rax-maas/blueflood/wiki

docs.featurebase.com

www.tencentcloud.com/document/product/1042

Developer

Apache Software Foundation and contributors

Rackspace

Molecula and Pilosa Open Source Contributors

Tencent

Initial release

2015

2013

2017

2013

Current release

1.0.0, September 2023

2022, May 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

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

Java

Server operating systems

All OS with a Java JDK11 or higher

Linux
OS X

Linux
macOS

hosted

Data scheme

yes

predefined scheme

yes

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

SQL queries

yes

APIs and other access methods

JDBC

HTTP REST

gRPC
JDBC
Kafka Connector
ODBC

JDBC
ODBC

Supported programming languages

Go
Java
Python

Java
Python

C
C#
C++
Java
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

based on Cassandra

Sharding

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

Multi-source replication
Source-replica 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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using Linux fsync

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

Users with fine-grained authorization concept

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