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DBMS > Amazon Aurora vs. Google Cloud Datastore vs. LevelDB vs. Microsoft Access vs. VictoriaMetrics

System Properties Comparison Amazon Aurora vs. Google Cloud Datastore vs. LevelDB vs. Microsoft Access vs. VictoriaMetrics

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonLevelDB  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)A fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelRelational DBMSDocument storeKey-value storeRelational DBMSTime Series DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.57
Rank#51  Overall
#32  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score2.25
Rank#115  Overall
#19  Key-value stores
Score101.16
Rank#11  Overall
#8  Relational DBMS
Score1.23
Rank#172  Overall
#15  Time Series DBMS
Websiteaws.amazon.com/­rds/­auroracloud.google.com/­datastoregithub.com/­google/­leveldbwww.microsoft.com/­en-us/­microsoft-365/­accessvictoriametrics.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlcloud.google.com/­datastore/­docsgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddeveloper.microsoft.com/­en-us/­accessdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperAmazonGoogleGoogleMicrosoftVictoriaMetrics
Initial release20152008201119922018
Current release1.23, February 20211902 (16.0.11328.20222), March 2019v1.91, May 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSDcommercial infoBundled with Microsoft OfficeOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++Go
Server operating systemshostedhostedIllumos
Linux
OS X
Windows
Windows infoNot a real database server, but making use of DLLsFreeBSD
Linux
macOS
OpenBSD
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes, details herenoyes
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.yesnonono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyesSQL-like query language (GQL)noyes infobut not compliant to any SQL standardno
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
DAO
ODBC
OLE DB
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
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
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Server-side scripts infoStored proceduresyesusing Google App Enginenoyes infosince Access 2010 using the ACE-engineno
TriggersyesCallbacks using the Google Apps Enginenoyes infosince Access 2010 using the ACE-engineno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication using PaxosnonenoneSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong 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 ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID infobut no files for transaction loggingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyes infobut no files for transaction loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono infoa simple user-level security was built in till version Access 2003

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More resources
Amazon AuroraGoogle Cloud DatastoreLevelDBMicrosoft AccessVictoriaMetrics
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