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DBMS > Amazon Aurora vs. Google BigQuery vs. Hypertable vs. RavenDB

System Properties Comparison Amazon Aurora vs. Google BigQuery vs. Hypertable vs. RavenDB

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonHypertable  Xexclude from comparisonRavenDB  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonLarge scale data warehouse service with append-only tablesAn open source BigTable implementation based on distributed file systems such as HadoopOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelRelational DBMSRelational DBMSWide column storeDocument store
Secondary database modelsDocument storeGraph DBMS
Spatial 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
Score60.38
Rank#19  Overall
#13  Relational DBMS
Score2.92
Rank#101  Overall
#18  Document stores
Websiteaws.amazon.com/­rds/­auroracloud.google.com/­bigqueryravendb.net
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlcloud.google.com/­bigquery/­docsravendb.net/­docs
DeveloperAmazonGoogleHypertable Inc.Hibernating Rhinos
Initial release2015201020092010
Current release0.9.8.11, March 20165.4, July 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGNU version 3. Commercial license availableOpen Source infoAGPL version 3, commercial license available
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 languageC++C#
Server operating systemshostedhostedLinux
OS X
Windows infoan inofficial Windows port is available
Linux
macOS
Raspberry Pi
Windows
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnono
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.yesno
Secondary indexesyesnorestricted infoonly exact value or prefix value scansyes
SQL infoSupport of SQLyesyesnoSQL-like query language (RQL)
APIs and other access methodsADO.NET
JDBC
ODBC
RESTful HTTP/JSON APIC++ API
Thrift
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
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
Java
JavaScript
Objective-C
PHP
Python
Ruby
C++
Java
Perl
PHP
Python
Ruby
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesuser defined functions infoin JavaScriptnoyes
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factor on file system levelMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoSince BigQuery is designed for querying datanoACID, Cluster-wide transaction available
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.yesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)noAuthorization levels configured per client per database

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More resources
Amazon AuroraGoogle BigQueryHypertableRavenDB
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