DBMS > Hyprcubd vs. IBM Db2 Event Store vs. OpenTSDB vs. ToroDB

System Properties Comparison Hyprcubd vs. IBM Db2 Event Store vs. OpenTSDB vs. ToroDB

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Editorial information provided by DB-Engines

Name

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

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Serverless Time Series DBMS

Distributed Event Store optimized for Internet of Things use cases

Scalable Time Series DBMS based on HBase

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Time Series DBMS

Event Store
Time Series DBMS

Time Series DBMS

Document store

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

Score	0.18
Rank	#315	Overall
	#2	Event Stores
	#26	Time Series DBMS

Score	1.59
Rank	#140	Overall
	#12	Time Series DBMS

Website

hyprcubd.com (offline)

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

opentsdb.net

github.com/torodb/server

Technical documentation

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

opentsdb.net/docs/build/html/index.html

Developer

Hyprcubd, Inc.

IBM

currently maintained by Yahoo and other contributors

8Kdata

Initial release

2017

2011

2016

Current release

2.0

License

Commercial or Open Source

commercial

free developer edition available

Open Source

LGPL

Open Source

AGPL-V3

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

C and C++

Java

Server operating systems

hosted

Linux

Linux, macOS, Windows for the developer addition

Linux
Windows

All OS with a Java 7 VM

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

yes

numeric data for metrics, strings for tags

yes

string, integer, double, boolean, date, object_id

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

SQL

Support of SQL

SQL-like query language

yes

through the embedded Spark runtime

APIs and other access methods

gRPC (https)

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

HTTP API
Telnet API

Supported programming languages

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

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

selectable replication factor

based on HBase

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

based on HBase

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

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 for users and roles

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

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Recent citations in the news

Hyprcubd CEO: From psychotherapist to tech startup founder
8 January 2021, The Business Journals

provided by Google News

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11 December 2023, IBM Research

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5 August 2016, KDnuggets

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1 June 2016, The New Stack

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