DBMS > Heroic vs. Hyprcubd vs. IBM Db2 Event Store vs. Linter vs. UniData,UniVerse

System Properties Comparison Heroic vs. Hyprcubd vs. IBM Db2 Event Store vs. Linter vs. UniData,UniVerse

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

Distributed Event Store optimized for Internet of Things use cases

RDBMS for high security requirements

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Time Series DBMS

Event Store
Time Series DBMS

Relational DBMS

Multivalue DBMS

Secondary database models

Spatial DBMS

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

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	3.16
Rank	#97	Overall
	#2	Multivalue DBMS

Website

github.com/spotify/heroic

hyprcubd.com (offline)

www.ibm.com/products/db2-event-store

linter.ru

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

spotify.github.io/heroic

www.ibm.com/docs/en/db2-event-store

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Spotify

Hyprcubd, Inc.

IBM

relex.ru

Rocket Software

Initial release

2014

2017

1990

1985

Current release

2.0

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free developer edition available

commercial

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

C and C++

Server operating systems

hosted

Linux

Linux, macOS, Windows for the developer addition

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

yes

optional

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

SQL-like query language

yes

through the embedded Spark runtime

yes

APIs and other access methods

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

gRPC (https)

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

yes

Triggers

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Active-active shard replication

Source-replica replication

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

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

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

Access rights according to SQL-standard and operating system based

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