DBMS > Heroic vs. Hyprcubd vs. Ingres vs. Oracle Coherence vs. Warp 10

System Properties Comparison Heroic vs. Hyprcubd vs. Ingres vs. Oracle Coherence vs. Warp 10

Editorial information provided by DB-Engines

Name

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

Description

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

Serverless Time Series DBMS

Well established RDBMS

Oracles in-memory data grid solution

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

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

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

github.com/spotify/heroic

hyprcubd.com (offline)

www.actian.com/databases/ingres

www.oracle.com/java/coherence

www.warp10.io

Technical documentation

spotify.github.io/heroic

docs.actian.com/ingres

docs.oracle.com/en/middleware/standalone/coherence

www.warp10.io/content/02_Getting_started

Developer

Spotify

Hyprcubd, Inc.

Actian Corporation

Oracle

SenX

Initial release

2014

1974

originally developed at University Berkely in early 1970s

2007

2015

Current release

11.2, May 2022

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache License 2.0

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

hosted

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

All OS with a Java VM

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

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

gRPC (https)

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

JCache
JPA
RESTful HTTP API

HTTP API
Jupyter
WebSocket

Supported programming languages

.Net
C++
Java

Server-side scripts

Stored procedures

yes

WarpScript

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Ingres Replicator

yes, with selectable consistency level

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

yes

optionally

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

token access

fine grained access rights according to SQL-standard

authentification to access the cache via certificates or http basic authentication

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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