DBMS > Google Cloud Datastore vs. Pinecone vs. searchxml vs. Tkrzw

System Properties Comparison Google Cloud Datastore vs. Pinecone vs. searchxml vs. Tkrzw

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Editorial information provided by DB-Engines

Name

Description

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

A managed, cloud-native vector database

DBMS for structured and unstructured content wrapped with an application server

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Document store

Vector DBMS

Native XML DBMS
Search engine

Key-value store

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

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	3.23
Rank	#92	Overall
	#3	Vector DBMS

Score	0.03
Rank	#390	Overall
	#7	Native XML DBMS
	#24	Search engines

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

cloud.google.com/datastore

www.pinecone.io

www.searchxml.net/category/products

dbmx.net/tkrzw

Technical documentation

cloud.google.com/datastore/docs

docs.pinecone.io/docs/overview

www.searchxml.net/support/handouts

Developer

Google

Pinecone Systems, Inc

informationpartners gmbh

Mikio Hirabayashi

Initial release

2008

2019

2015

2020

Current release

1.0

0.9.3, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

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++

Server operating systems

hosted

Windows

Linux
macOS

Data scheme

schema-free

Typing

predefined data types such as float or date

yes, details here

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

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (GQL)

APIs and other access methods

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

RESTful HTTP API

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Python

C++

most other programming languages supported via APIs

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

using Google App Engine

yes

on the application server

Triggers

Callbacks using the Google Apps Engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

yes

sychronisation to multiple collections

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

multiple readers, single writer

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

using specific database classes

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Domain, group and role-based access control at the document level and for application services

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More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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