DBMS > Altibase vs. Axibase vs. Databricks vs. Google BigQuery vs. TimesTen

System Properties Comparison Altibase vs. Axibase vs. Databricks vs. Google BigQuery vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

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

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Primary database model

Relational DBMS

Time Series DBMS

Document store
Relational DBMS

Relational DBMS

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

Score	0.87
Rank	#200	Overall
	#93	Relational DBMS

Score	0.21
Rank	#308	Overall
	#25	Time Series DBMS

Score	84.24
Rank	#14	Overall
	#2	Document stores
	#9	Relational DBMS

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

altibase.com

axibase.com/docs/atsd/finance

www.databricks.com

cloud.google.com/bigquery

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

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

docs.databricks.com

cloud.google.com/bigquery/docs

docs.oracle.com/en/database/other-databases/timesten/index.html

Developer

Altibase

Axibase Corporation

Databricks

Google

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

1999

2013

2010

1998

Current release

v7.3, 2023, August 2023

15585

Release 22.1

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

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

Linux

hosted

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Data scheme

yes

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

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, 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.

yes

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL-92

SQL-like query language

with Databricks SQL

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

RESTful HTTP/JSON API

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

C
C++
Java

Go
Java
PHP
Python
R
Ruby

Python
R
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C++
Java
Node.js
PL/SQL
Python

Server-side scripts

Stored procedures

stored procedures and stored functions

yes

user defined functions and aggregates

user defined functions

in JavaScript

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

by means of logfiles and checkpoints

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)

fine grained access rights according to SQL-standard

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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