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DBMS > AlaSQL vs. Amazon Neptune vs. Firebolt vs. Google Cloud Datastore vs. jBASE

System Properties Comparison AlaSQL vs. Amazon Neptune vs. Firebolt vs. Google Cloud Datastore vs. jBASE

Editorial information provided by DB-Engines
NameAlaSQL  Xexclude from comparisonAmazon Neptune  Xexclude from comparisonFirebolt  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonjBASE  Xexclude from comparison
DescriptionJavaScript DBMS libraryFast, reliable graph database built for the cloudHighly scalable cloud data warehouse and analytics product infoForked from ClickhouseAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA robust multi-value DBMS comprising development tools and middleware
Primary database modelDocument store
Relational DBMS
Graph DBMS
RDF store
Relational DBMSDocument storeMultivalue DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.51
Rank#256  Overall
#40  Document stores
#118  Relational DBMS
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score1.73
Rank#140  Overall
#63  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score1.49
Rank#156  Overall
#3  Multivalue DBMS
Websitealasql.orgaws.amazon.com/­neptunewww.firebolt.iocloud.google.com/­datastorewww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbase
Technical documentationgithub.com/­AlaSQL/­alasqlaws.amazon.com/­neptune/­developer-resourcesdocs.firebolt.iocloud.google.com/­datastore/­docsdocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9
DeveloperAndrey Gershun & Mathias R. WulffAmazonFirebolt Analytics Inc.GoogleRocket Software (formerly Zumasys)
Initial release20142017202020081991
Current release5.7
License infoCommercial or Open SourceOpen Source infoMIT-Licensecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScript
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)hostedhostedhostedAIX
Linux
Windows
Data schemeschema-freeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or datenoyesyesyes, details hereoptional
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.nononoyes
Secondary indexesnonoyesyes
SQL infoSupport of SQLClose to SQL99, but no user access control, stored procedures and host language bindings.noyesSQL-like query language (GQL)Embedded SQL for jBASE in BASIC
APIs and other access methodsJavaScript APIOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
.Net
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
Supported programming languagesJavaScriptC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Go
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Basic
Jabbascript
Java
Server-side scripts infoStored proceduresnononousing Google App Engineyes
TriggersyesnonoCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.depending on storage layerMulti-source replication using Paxosyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
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.
Foreign keys infoReferential integrityyesyes infoRelationships in graphsyes infovia ReferenceProperties or Ancestor pathsno
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 TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes infoby using IndexedDB, SQL.JS or proprietary FileStorageyes infowith encyption-at-restyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlnoAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights can be defined down to the item level

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More resources
AlaSQLAmazon NeptuneFireboltGoogle Cloud DatastorejBASE
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