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DBMS > Amazon Aurora vs. Google Cloud Datastore vs. GreptimeDB vs. Spark SQL

System Properties Comparison Amazon Aurora vs. Google Cloud Datastore vs. GreptimeDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGreptimeDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAn open source Time Series DBMS built for increased scalability, high performance and efficiencySpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument storeTime Series DBMSRelational 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
Score0.12
Rank#351  Overall
#34  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­rds/­auroracloud.google.com/­datastoregreptime.comspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlcloud.google.com/­datastore/­docsdocs.greptime.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonGoogleGreptime Inc.Apache Software Foundation
Initial release2015200820222014
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustScala
Server operating systemshostedhostedAndroid
Docker
FreeBSD
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeyesschema-freeschema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyes
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 indexesyesyesyesno
SQL infoSupport of SQLyesSQL-like query language (GQL)yesSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
gRPC
HTTP API
JDBC
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
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Erlang
Go
Java
JavaScript
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesusing Google App EnginePythonno
TriggersyesCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowno
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 Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
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.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)Simple rights management via user accountsno
More information provided by the system vendor
Amazon AuroraGoogle Cloud DatastoreGreptimeDBSpark SQL
Specific characteristicsGreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more
Competitive advantages- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more
Typical application scenariosFor IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more
Key customersGreptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more
Market metricsGreptimeDB has garnered global recognition by topping GitHub trends following its...
» more
Licensing and pricing modelsGreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

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More resources
Amazon AuroraGoogle Cloud DatastoreGreptimeDBSpark SQL
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