DBMS > Heroic vs. XTDB vs. YTsaurus

System Properties Comparison Heroic vs. XTDB vs. YTsaurus

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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

A general purpose database with bitemporal SQL and Datalog and graph queries

YTsaurus is an open source platform for distributed storage and processing.

Primary database model

Time Series DBMS

Document store

Document store
Key-value store

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

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Score	0.21
Rank	#324	Overall
	#45	Document stores
	#48	Key-value stores

Website

github.com/spotify/heroic

github.com/xtdb/xtdb
www.xtdb.com

ytsaurus.tech

Technical documentation

spotify.github.io/heroic

www.xtdb.com/docs

ytsaurus.tech/docs/en

Developer

Spotify

Juxt Ltd.

Yandex

Initial release

2014

2019

2023

Current release

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

MIT License

Open Source

Apache License, Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Clojure

C++

Server operating systems

All OS with a Java 8 (and higher) VM
Linux

Ubuntu

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

yes

SQL

Support of SQL

limited SQL, making use of Apache Calcite

YQL, an SQL-based language, is supported

APIs and other access methods

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

HTTP REST
JDBC

Supported programming languages

Clojure
Java

C++
Go
Java
JavaScript
Python

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, each node contains all data

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Access Control Lists

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