DBMS > Pinecone vs. Snowflake vs. XTDB

System Properties Comparison Pinecone vs. Snowflake vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

A managed, cloud-native vector database

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Vector DBMS

Relational DBMS

Document store

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

Score	3.23
Rank	#92	Overall
	#2	Vector DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.pinecone.io

www.snowflake.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.pinecone.io/docs/overview

docs.snowflake.net/manuals/index.html

www.xtdb.com/docs

Developer

Pinecone Systems, Inc

Snowflake Computing Inc.

Juxt Ltd.

Initial release

2019

2014

2019

Current release

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Clojure

Server operating systems

hosted

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

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

schema-free

Typing

predefined data types such as float or date

String, Number, Boolean

yes

yes, extensible-data-notation format

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

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

RESTful HTTP API

CLI Client
JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

Python

JavaScript (Node.js)
Python

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, each node contains all data

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

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

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

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

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