DBMS > GBase vs. Hawkular Metrics vs. JaguarDB vs. Warp 10

System Properties Comparison GBase vs. Hawkular Metrics vs. JaguarDB vs. Warp 10

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Editorial information provided by DB-Engines

Name

Description

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

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

Performant, highly scalable DBMS for AI and IoT applications

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Relational DBMS

Time Series DBMS

Key-value store
Vector DBMS

Time Series DBMS

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

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#14	Vector DBMS

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

Technical documentation

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

www.jaguardb.com/support.html

www.warp10.io/content/02_Getting_started

Developer

General Data Technology Co., Ltd.

Community supported by Red Hat

DataJaguar, Inc.

SenX

Initial release

2004

2014

2015

Current release

GBase 8a, GBase 8s, GBase 8c

3.3 July 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPL V3.0

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C, Java, Python

Java

C++

the server part. Clients available in other languages

Java

Server operating systems

Linux

Linux
OS X
Windows

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

schema-free

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

SQL

Support of SQL

Standard with numerous extensions

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

HTTP REST

JDBC
ODBC

HTTP API
Jupyter
WebSocket

Supported programming languages

Go
Java
Python
Ruby

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

user defined functions

yes

WarpScript

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

based on Cassandra

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

Multi-source replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Immediate Consistency

based on HBase

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

rights management via user accounts

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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