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DBMS > Amazon Aurora vs. etcd vs. HEAVY.AI vs. Kinetica vs. Microsoft Azure Synapse Analytics

System Properties Comparison Amazon Aurora vs. etcd vs. HEAVY.AI vs. Kinetica vs. Microsoft Azure Synapse Analytics

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonetcd  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonA distributed reliable key-value storeA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully vectorized database across both GPUs and CPUsElastic, large scale data warehouse service leveraging the broad eco-system of SQL Server
Primary database modelRelational DBMSKey-value storeRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score7.25
Rank#54  Overall
#5  Key-value stores
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Websiteaws.amazon.com/­rds/­auroraetcd.io
github.com/­etcd-io/­etcd
github.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.comazure.microsoft.com/­services/­synapse-analytics
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmletcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.heavy.aidocs.kinetica.comdocs.microsoft.com/­azure/­synapse-analytics
DeveloperAmazonHEAVY.AI, Inc.KineticaMicrosoft
Initial release2015201620122016
Current release3.4, August 20195.10, January 20227.1, August 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2; enterprise edition availablecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++ and CUDAC, C++C++
Server operating systemshostedFreeBSD
Linux
Windows infoexperimental
LinuxLinuxhosted
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesnoyesyesyes
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.yesnononono
Secondary indexesyesnonoyesyes
SQL infoSupport of SQLyesnoyesSQL-like DML and DDL statementsyes
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC
JSON over HTTP
JDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
All languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
C#
Java
PHP
Server-side scripts infoStored proceduresyesnonouser defined functionsTransact SQL
Triggersyesyes, watching key changesnoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infoRound robinShardingSharding, horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replicationSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesnonoyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraints
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standardAccess rights for users and roles on table levelyes

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More resources
Amazon AuroraetcdHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KineticaMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
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