DBMS > Google BigQuery vs. Pinecone vs. UniData,UniVerse

System Properties Comparison Google BigQuery vs. Pinecone vs. UniData,UniVerse

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

A managed, cloud-native vector database

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Relational DBMS

Vector DBMS

Multivalue DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	3.23
Rank	#92	Overall
	#3	Vector DBMS

Score	2.85
Rank	#98	Overall
	#1	Multivalue DBMS

Website

cloud.google.com/bigquery

www.pinecone.io

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

Technical documentation

cloud.google.com/bigquery/docs

docs.pinecone.io/docs/overview

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Google

Pinecone Systems, Inc

Rocket Software

Initial release

2010

2019

1985

License

Commercial or Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Server operating systems

hosted

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

String, Number, Boolean

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP/JSON API

RESTful HTTP API

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Python

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

configurable

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

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

Google Cloud Identity & Access Management (IAM)

Access rights according to SQL-standard and operating system based

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