DBMS > Altibase vs. Apache Druid vs. Snowflake vs. Teradata Aster

System Properties Comparison Altibase vs. Apache Druid vs. Snowflake vs. Teradata Aster

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

An enterprise grade, high-performance RDBMS

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Cloud-based data warehousing service for structured and semi-structured data

Platform for big data analytics on multistructured data sources and types

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Relational DBMS

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

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

altibase.com

druid.apache.org

www.snowflake.com

Technical documentation

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

druid.apache.org/docs/latest/design

docs.snowflake.net/manuals/index.html

Developer

Altibase

Apache Software Foundation and contributors

Snowflake Computing Inc.

Teradata

Initial release

1999

2012

2014

2005

Current release

v7.3, 2023, August 2023

29.0.1, April 2024

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Apache license v2

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
OS X
Unix

hosted

Linux

Data scheme

yes

schema-less columns are supported

yes

support of semi-structured data formats (JSON, XML, Avro)

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

defined schema within the relational store; partial schema or schema free in the Aster File Store

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

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL-92

SQL for querying

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol

JDBC
RESTful HTTP/JSON API

CLI Client
JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C
C++
Java

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

JavaScript (Node.js)
Python

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

stored procedures and stored functions

user defined functions

R packages

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, via HDFS, S3 or other storage engines

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

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

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Users with fine-grained authorization concept, user roles and pluggable authentication

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.