DBMS > Apache Pinot vs. Hyprcubd vs. ReductStore

System Properties Comparison Apache Pinot vs. Hyprcubd vs. ReductStore

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Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

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

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Primary database model

Relational DBMS

Time Series DBMS

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

Score	0.40
Rank	#270	Overall
	#125	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

pinot.apache.org

hyprcubd.com (offline)

github.com/reductstore
www.reduct.store

Technical documentation

docs.pinot.apache.org

www.reduct.store/docs

Developer

Apache Software Foundation and contributors

Hyprcubd, Inc.

ReductStore LLC

Initial release

2015

2023

Current release

1.0.0, September 2023

1.9, March 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Business Source License 1.1

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++, Rust

Server operating systems

All OS with a Java JDK11 or higher

hosted

Docker
Linux
macOS
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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

SQL

Support of SQL

SQL-like query language

APIs and other access methods

JDBC

gRPC (https)

HTTP API

Supported programming languages

Go
Java
Python

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

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

token access

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More resources

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