DBMS > Heroic vs. Hypertable vs. SAP HANA vs. XTDB

System Properties Comparison Heroic vs. Hypertable vs. SAP HANA vs. XTDB

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

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

An open source BigTable implementation based on distributed file systems such as Hadoop

In-memory, column based data store. Available as appliance or cloud service

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

Primary database model

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

github.com/spotify/heroic

www.sap.com/products/hana.html

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

Technical documentation

spotify.github.io/heroic

help.sap.com/hana

www.xtdb.com/docs

Developer

Spotify

Hypertable Inc.

SAP

Juxt Ltd.

Initial release

2014

2009

2010

2019

Current release

0.9.8.11, March 2016

2.0 SPS07 (April 4, 2023), April 2023

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GNU version 3. Commercial license available

commercial

Open Source

MIT License

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Clojure

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

Appliance or cloud-service

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

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

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

C++ API
Thrift

JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

Clojure
Java

Server-side scripts

Stored procedures

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor on file system level

yes

yes, each node contains all data

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

Immediate Consistency

Foreign keys

Referential integrity

yes

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

In-memory capabilities

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

yes

User concepts

Access control

yes

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