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DBMS > AlaSQL vs. Amazon Aurora vs. Google Cloud Datastore vs. jBASE vs. Kinetica

System Properties Comparison AlaSQL vs. Amazon Aurora vs. Google Cloud Datastore vs. jBASE vs. Kinetica

Editorial information provided by DB-Engines
NameAlaSQL  Xexclude from comparisonAmazon Aurora  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonjBASE  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionJavaScript DBMS libraryMySQL and PostgreSQL compatible cloud service by AmazonAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA robust multi-value DBMS comprising development tools and middlewareFully vectorized database across both GPUs and CPUs
Primary database modelDocument store
Relational DBMS
Relational DBMSDocument storeMultivalue DBMSRelational DBMS
Secondary database modelsDocument storeSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.46
Rank#260  Overall
#40  Document stores
#121  Relational DBMS
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score1.41
Rank#159  Overall
#3  Multivalue DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websitealasql.orgaws.amazon.com/­rds/­auroracloud.google.com/­datastorewww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbasewww.kinetica.com
Technical documentationgithub.com/­AlaSQL/­alasqldocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlcloud.google.com/­datastore/­docsdocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9docs.kinetica.com
DeveloperAndrey Gershun & Mathias R. WulffAmazonGoogleRocket Software (formerly Zumasys)Kinetica
Initial release20142015200819912012
Current release5.77.1, August 2021
License infoCommercial or Open SourceOpen Source infoMIT-Licensecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScriptC, C++
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)hostedhostedAIX
Linux
Windows
Linux
Data schemeschema-freeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or datenoyesyes, details hereoptionalyes
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.noyesnoyesno
Secondary indexesnoyesyesyes
SQL infoSupport of SQLClose to SQL99, but no user access control, stored procedures and host language bindings.yesSQL-like query language (GQL)Embedded SQL for jBASE in BASICSQL-like DML and DDL statements
APIs and other access methodsJavaScript APIADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesJavaScriptAda
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
.Net
Basic
Jabbascript
Java
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoyesusing Google App Engineyesuser defined functions
TriggersyesyesCallbacks using the Google Apps Engineyesyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioningShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationMulti-source replication using PaxosyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate 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 or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesyesyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infoonly for local storage and DOM-storageACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infoby using IndexedDB, SQL.JS or proprietary FileStorageyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights can be defined down to the item levelAccess rights for users and roles on table level

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More resources
AlaSQLAmazon AuroraGoogle Cloud DatastorejBASEKinetica
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