DBMS > Altibase vs. Databricks vs. Google BigQuery vs. Hawkular Metrics vs. jBASE

System Properties Comparison Altibase vs. Databricks vs. Google BigQuery vs. Hawkular Metrics vs. jBASE

Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

Large scale data warehouse service with append-only tables

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

A robust multi-value DBMS comprising development tools and middleware

Primary database model

Relational DBMS

Document store
Relational DBMS

Relational DBMS

Time Series DBMS

Multivalue DBMS

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

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	78.61
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Website

altibase.com

www.databricks.com

cloud.google.com/bigquery

www.hawkular.org

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

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

docs.databricks.com

cloud.google.com/bigquery/docs

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

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

Developer

Altibase

Databricks

Google

Community supported by Red Hat

Rocket Software (formerly Zumasys)

Initial release

1999

2013

2010

2014

1991

Current release

v7.3, 2023, August 2023

5.7

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

Open Source

Apache 2.0

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++

Java

Server operating systems

AIX
HP-UX
Linux

hosted

Linux
OS X
Windows

AIX
Linux
Windows

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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

ANSI SQL-92

with Databricks SQL

yes

Embedded SQL for jBASE in BASIC

APIs and other access methods

JDBC
ODBC
Proprietary protocol

JDBC
ODBC
RESTful HTTP API

RESTful HTTP/JSON API

HTTP REST

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

C
C++
Java

Python
R
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Go
Java
Python
Ruby

.Net
Basic
Jabbascript
Java

Server-side scripts

Stored procedures

stored procedures and stored functions

user defined functions and aggregates

user defined functions

in JavaScript

yes

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

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

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying 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

fine grained access rights according to SQL-standard

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights can be defined down to the item level

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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