DBMS > Amazon DynamoDB vs. Pinecone vs. Snowflake vs. Transbase

System Properties Comparison Amazon DynamoDB vs. Pinecone vs. Snowflake vs. Transbase

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Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

A managed, cloud-native vector database

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

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Document store
Key-value store

Vector DBMS

Relational DBMS

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

Score	70.06
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	3.02
Rank	#87	Overall
	#3	Vector DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Score	0.05
Rank	#355	Overall
	#150	Relational DBMS

Website

aws.amazon.com/dynamodb

www.pinecone.io

www.snowflake.com

www.transaction.de/en/products/transbase.html

Technical documentation

docs.aws.amazon.com/dynamodb

docs.pinecone.io/docs/overview

docs.snowflake.net/manuals/index.html

www.transaction.de/en/products/transbase/features.html

Developer

Amazon

Pinecone Systems, Inc

Snowflake Computing Inc.

Transaction Software GmbH

Initial release

2012

2019

2014

1987

Current release

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

free development license

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 and C++

Server operating systems

hosted

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

yes

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

yes

Typing

predefined data types such as float or date

yes

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

yes

APIs and other access methods

RESTful HTTP API

CLI Client
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Python

JavaScript (Node.js)
Python

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

by integration with AWS Lambda

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

yes

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 rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

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

fine grained access rights according to SQL-standard

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