DBMS > Pinecone vs. Postgres-XL vs. Snowflake vs. Teradata Aster

System Properties Comparison Pinecone vs. Postgres-XL vs. Snowflake vs. Teradata Aster

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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

A managed, cloud-native vector database

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

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

Vector DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	3.23
Rank	#92	Overall
	#3	Vector DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

www.pinecone.io

www.postgres-xl.org

www.snowflake.com

Technical documentation

docs.pinecone.io/docs/overview

www.postgres-xl.org/documentation

docs.snowflake.net/manuals/index.html

Developer

Pinecone Systems, Inc

Snowflake Computing Inc.

Teradata

Initial release

2019

2014

since 2012, originally named StormDB

2014

2005

Current release

10 R1, October 2018

License

Commercial or Open Source

commercial

Open Source

Mozilla public license

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

Server operating systems

hosted

Linux
macOS

hosted

Linux

Data scheme

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

String, Number, Boolean

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

XML type, but no XML query functionality

yes

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

yes

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

CLI Client
JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

JavaScript (Node.js)
Python

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

user defined functions

R packages

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

MVCC

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.

User concepts

Access control

fine grained access rights according to SQL-standard

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

fine grained access rights according to SQL-standard

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