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DBMS > Amazon Aurora vs. Pinecone vs. YottaDB

System Properties Comparison Amazon Aurora vs. Pinecone vs. YottaDB

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonPinecone  Xexclude from comparisonYottaDB  Xexclude from comparison
DescriptionFully managed relational database service built for the cloud providing unparalleled high performance and availability at global scale for MySQL, PostgreSQL, and DSQLA managed, cloud-native vector databaseA fast and solid embedded Key-value store
Primary database modelRelational DBMSVector DBMSKey-value store
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Relational DBMS infousing the Octo plugin
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.33
Rank#46  Overall
#29  Relational DBMS
Score3.34
Rank#77  Overall
#6  Vector DBMS
Score0.18
Rank#313  Overall
#46  Key-value stores
Websiteaws.amazon.com/­rds/­aurorawww.pinecone.ioyottadb.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_AuroraOverview.html
docs.aws.amazon.com/­aurora-dsql/­latest/­userguide/­what-is-aurora-dsql.html
docs.pinecone.io/­docs/­overviewyottadb.com/­resources/­documentation
Social network pagesLinkedIn
DeveloperAmazonPinecone Systems, IncYottaDB, LLC
Initial release201520192001
Current releaseAurora DSQL, November 2024 (preview), PostgreSQL: docs.aws.amazon.com/­AmazonRDS/­latest/­AuroraPostgreSQLReleaseNotes/­AuroraPostgreSQL.Updates.html , MySQL: docs.aws.amazon.com/­AmazonRDS/­latest/­AuroraMySQLReleaseNotes/­AuroraMySQL.release-calendars.html
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL 3.0
Cloud-based only infoOnly available as a cloud serviceyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languagePostgreSQL/MySQL: C, C++, Aurora DSQL: RustC
Server operating systemsAmazon LinuxhostedDocker
Linux
Data schemeyesschema-free
Typing infopredefined data types such as float or dateyesString, Number, Booleanno
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yesnono
Secondary indexesyesno
SQL infoSupport of SQLyes, MySQL and PostgreSQL dialectsnoby using the Octo plugin
APIs and other access methodsDSQL API: docs.aws.amazon.com/­aurora-dsql/­latest/­userguide/­CHAP_api_reference.html
MySQL wire protocol
PostgreSQL wire protocol
RDS Data API: docs.aws.amazon.com/­AmazonRDS/­latest/­UserGuide/­ProgrammingGuide.html
RESTful HTTP APIPostgreSQL wire protocol infousing the Octo plugin
Proprietary protocol
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Rust
Scheme
Tcl
PythonC
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust
Server-side scripts infoStored proceduresPL/pgSQL, MySQL stored program language, APG trusted language extensions
TriggersAurora MySQL: Yes. Aurora PostgreSQL: Yes. Aurora DSQL: No.
Partitioning methods infoMethods for storing different data on different nodesDBMS table partitioning, Horizontal storage partitioning, Sharding, Distributed horizontal partitioning (DSQL)
Replication methods infoMethods for redundantly storing data on multiple nodesFull replication
Logical replication
Snapshot replication
Transactional replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate/Strong Consistency
Foreign keys infoReferential integrityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID, Multi-statementoptimistic locking
Concurrency infoSupport for concurrent manipulation of dataMultiversion concurrency control (MVCC) with fully compatible MySQL and PostgreSQL options. Optimistic concurrency control (OCC) in Aurora DSQL.yes
Durability infoSupport for making data persistentData is replicated across 3 Availability Zones (AZs) within a single AWS Region. Active-active multi-Region high availability across 3 Regions (2 active, 1 witness) and automated failover recovery with Aurora DSQL. Automated, continuous backup of data with point in time restore. Fault-tolerant, self-healing storage system.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlRole based permissions
Row level security
Users and groups based on OS-security mechanisms

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More resources
Amazon AuroraPineconeYottaDB
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Recent citations in the news

Optimizing cost savings: The advantage of Amazon Aurora over self-managed open source databases
31 March 2025, Amazon Web Services

How Heroku migrated hundreds of thousands of self-managed PostgreSQL databases to Amazon Aurora
10 April 2025, Amazon Web Services

Introducing Amazon Aurora DSQL | Amazon Web Services
3 December 2024, Amazon Web Services

Amazon Aurora PostgreSQL Limitless Database is now generally available
31 October 2024, Amazon Web Services

Introducing scaling to 0 capacity with Amazon Aurora Serverless v2
20 November 2024, Amazon Web Services

provided by Google News

Pinecone turns unstructured data into knowledgeable AI for developers with Microsoft Azure
4 February 2025, Microsoft

Pinecone expands vector database with cascading retrieval, boosting enterprise AI accuracy by up to 48%
2 December 2024, VentureBeat

Pinecone integrates AI inferencing with vector database
2 December 2024, Blocks and Files

Pinecone Revamps Vector Database Architecture for AI Apps
27 February 2025, The New Stack

Pinecone Named to Fast Company's Annual List of the World's Most Innovative Companies of 2025
18 March 2025, PR Newswire

provided by Google News



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