DBMS > Hyprcubd vs. IBM Db2 Event Store vs. LevelDB vs. Trafodion

System Properties Comparison Hyprcubd vs. IBM Db2 Event Store vs. LevelDB vs. Trafodion

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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.

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Serverless Time Series DBMS

Distributed Event Store optimized for Internet of Things use cases

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Transactional SQL-on-Hadoop DBMS

Primary database model

Time Series DBMS

Event Store
Time Series DBMS

Key-value store

Relational DBMS

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

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

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Website

hyprcubd.com (offline)

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

github.com/google/leveldb

trafodion.apache.org

Technical documentation

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

github.com/google/leveldb/blob/main/doc/index.md

trafodion.apache.org/documentation.html

Developer

Hyprcubd, Inc.

IBM

Google

Apache Software Foundation, originally developed by HP

Initial release

2017

2011

2014

Current release

2.0

1.23, February 2021

2.3.0, February 2019

License

Commercial or Open Source

commercial

free developer edition available

Open Source

BSD

Open Source

Apache 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

C and C++

C++

C++, Java

Server operating systems

hosted

Linux

Linux, macOS, Windows for the developer addition

Illumos
Linux
OS X
Windows

Linux

Data scheme

yes

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

through the embedded Spark runtime

yes

APIs and other access methods

gRPC (https)

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

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

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

Java 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

Active-active shard replication

none

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual 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

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

with automatic compression on writes

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

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