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DBMS > Amazon Aurora vs. EsgynDB vs. Netezza vs. Qdrant

System Properties Comparison Amazon Aurora vs. EsgynDB vs. Netezza vs. Qdrant

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonEsgynDB  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonQdrant  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionData warehouse and analytics appliance part of IBM PureSystemsA high-performance vector database with neural network or semantic-based matching
Primary database modelRelational DBMSRelational DBMSRelational DBMSVector DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.84
Rank#44  Overall
#28  Relational DBMS
Score0.15
Rank#325  Overall
#144  Relational DBMS
Score7.56
Rank#48  Overall
#31  Relational DBMS
Score1.53
Rank#145  Overall
#7  Vector DBMS
Websiteaws.amazon.com/­rds/­aurorawww.esgyn.cnwww.ibm.com/­products/­netezzagithub.com/­qdrant/­qdrant
qdrant.tech
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlqdrant.tech/­documentation
DeveloperAmazonEsgynIBMQdrant
Initial release2015201520002021
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaRust
Server operating systemshostedLinuxLinux infoincluded in applianceDocker
Linux
macOS
Windows
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesNumbers, Strings, Geo, Boolean
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 indexesyesyesyesyes infoKeywords, numberic ranges, geo, full-text
SQL infoSupport of SQLyesyesyesno
APIs and other access methodsADO.NET
JDBC
ODBC
ADO.NET
JDBC
ODBC
JDBC
ODBC
OLE DB
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
All languages supporting JDBC/ODBC/ADO.NetC
C++
Fortran
Java
Lua
Perl
Python
R
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresyesJava Stored Proceduresyes
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication between multi datacentersSource-replica replicationCollection-level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency, tunable consistency
Foreign keys infoReferential integrityyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardUsers with fine-grained authorization conceptKey-based authentication

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More resources
Amazon AuroraEsgynDBNetezza infoAlso called PureData System for Analytics by IBMQdrant
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Recent citations in the news

Migrate SQL Server databases to Babelfish for Aurora PostgreSQL using change tracking with a linked server
24 September 2024, AWS Blog

Replace Amazon QLDB with Amazon Aurora PostgreSQL for audit use cases
18 July 2024, AWS Blog

Build generative AI applications with Amazon Aurora and Amazon Bedrock Knowledge Bases
2 February 2024, AWS Blog

Review your Amazon Aurora and Amazon RDS security configuration with Prowler’s new checks
6 August 2024, AWS Blog

Continuously replicate Amazon DynamoDB changes to Amazon Aurora PostgreSQL using AWS Lambda
14 May 2024, AWS Blog

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Unify and share data across Netezza and watsonx.data for new generative AI applications
21 June 2024, ibm.com

How to migrate a large data warehouse from IBM Netezza to Amazon Redshift with no downtime
21 August 2019, AWS Blog

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

Copy data from Netezza to Azure with Azure Data Factory
9 September 2019, Microsoft

IBM Completes Acquisition of Netezza
11 November 2010, PR Newswire

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Qdrant review: A highly flexible option for vector search
29 July 2024, InfoWorld

Open source vector database startup Qdrant raises $28M
23 January 2024, TechCrunch

Vector database company Qdrant wants RAG to be more cost-effective
2 July 2024, VentureBeat

Qdrant Announces an Industry-First Hybrid Cloud Offering For Enterprise AI Applications
16 April 2024, Business Wire

Qdrant unveils hybrid vector algorithm for improved RAG
2 July 2024, Blocks & Files

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