DBMS > HEAVY.AI vs. IBM Db2 Event Store vs. jBASE vs. TempoIQ

System Properties Comparison HEAVY.AI vs. IBM Db2 Event Store vs. jBASE vs. TempoIQ

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Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Distributed Event Store optimized for Internet of Things use cases

A robust multi-value DBMS comprising development tools and middleware

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Relational DBMS

Event Store
Time Series DBMS

Multivalue DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

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

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Website

github.com/heavyai/heavydb
www.heavy.ai

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

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

tempoiq.com (offline)

Technical documentation

docs.heavy.ai

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

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

Developer

HEAVY.AI, Inc.

IBM

Rocket Software (formerly Zumasys)

TempoIQ

Initial release

2016

2017

1991

2012

Current release

5.10, January 2022

2.0

5.7

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

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

C++ and CUDA

C and C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

AIX
Linux
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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.

yes

Secondary indexes

SQL

Support of SQL

yes

through the embedded Spark runtime

Embedded SQL for jBASE in BASIC

APIs and other access methods

JDBC
ODBC
Thrift
Vega

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

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

.Net
Basic
Jabbascript
Java

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Active-active shard replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

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

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

simple authentication-based access control

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