DBMS > Hawkular Metrics vs. SAP HANA vs. Teradata vs. Transwarp StellarDB

System Properties Comparison Hawkular Metrics vs. SAP HANA vs. Teradata vs. Transwarp StellarDB

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Editorial information provided by DB-Engines

Name

Description

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

In-memory, column based data store. Available as appliance or cloud service

A hybrid cloud data analytics software platform (Teradata Vantage)

A distributed graph DBMS built for enterprise-level graph applications

Primary database model

Time Series DBMS

Relational DBMS

Graph DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Score	0.07
Rank	#371	Overall
	#39	Graph DBMS

Website

www.hawkular.org

www.sap.com/products/hana.html

www.teradata.com

www.transwarp.cn/en/product/stellardb

Technical documentation

www.hawkular.org/hawkular-metrics/docs/user-guide

help.sap.com/hana

docs.teradata.com

Developer

Community supported by Red Hat

SAP

Teradata

Transwarp

Initial release

2014

2010

1984

Current release

2.0 SPS07 (April 4, 2023), April 2023

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

Linux
OS X
Windows

Appliance or cloud-service

hosted
Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes

SQL 2016 + extensions

SQL-like query language

APIs and other access methods

HTTP REST

JDBC
ODBC

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

OpenCypher

Supported programming languages

Go
Java
Python
Ruby

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

SQLScript, R

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

yes

Sharding

Hashing

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

Multi-source 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

based on Cassandra
Immediate Consistency

based on Cassandra

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

yes

Durability

Support for making data persistent

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

yes

fine grained access rights according to SQL-standard

yes

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