DBMS > Heroic vs. ReductStore

System Properties Comparison Heroic vs. ReductStore

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Editorial information provided by DB-Engines

Name

Description

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

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

Time Series DBMS

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Score	0.02
Rank	#373	Overall
	#40	Time Series DBMS

Score	0.07
Rank	#354	Overall
	#37	Time Series DBMS

Website

github.com/spotify/heroic

github.com/reductstore
www.reduct.store

Technical documentation

spotify.github.io/heroic

www.reduct.store/docs

Developer

Spotify

ReductStore LLC

Initial release

2014

2023

Current release

1.9, March 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Business Source License 1.1

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++, Rust

Server operating systems

Docker
Linux
macOS
Windows

Data scheme

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

via Elasticsearch

SQL

Support of SQL

APIs and other access methods

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

HTTP API

Supported programming languages

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate 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

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.

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Recent citations in the news

How Code Wizards load tested Heroic Labs’ Nakama to two million concurrent players with AWS
1 October 2024, AWS Blog

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