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DBMS > AlaSQL vs. Google Cloud Datastore vs. HugeGraph vs. JaguarDB vs. Lovefield

System Properties Comparison AlaSQL vs. Google Cloud Datastore vs. HugeGraph vs. JaguarDB vs. Lovefield

Editorial information provided by DB-Engines
NameAlaSQL  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHugeGraph  Xexclude from comparisonJaguarDB  Xexclude from comparisonLovefield  Xexclude from comparison
DescriptionJavaScript DBMS libraryAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA fast-speed and highly-scalable Graph DBMSPerformant, highly scalable DBMS for AI and IoT applicationsEmbeddable relational database for web apps written in pure JavaScript
Primary database modelDocument store
Relational DBMS
Document storeGraph DBMSKey-value store
Vector DBMS
Relational 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
Score4.47
Rank#76  Overall
#12  Document stores
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
#13  Vector DBMS
Score0.29
Rank#293  Overall
#133  Relational DBMS
Websitealasql.orgcloud.google.com/­datastoregithub.com/­hugegraph
hugegraph.apache.org
www.jaguardb.comgoogle.github.io/­lovefield
Technical documentationgithub.com/­AlaSQL/­alasqlcloud.google.com/­datastore/­docshugegraph.apache.org/­docswww.jaguardb.com/­support.htmlgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.md
DeveloperAndrey Gershun & Mathias R. WulffGoogleBaiduDataJaguar, Inc.Google
Initial release20142008201820152014
Current release0.93.3 July 20232.1.12, February 2017
License infoCommercial or Open SourceOpen Source infoMIT-LicensecommercialOpen Source infoApache Version 2.0Open Source infoGPL V3.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScriptJavaC++ infothe server part. Clients available in other languagesJavaScript
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)hostedLinux
macOS
Unix
Linuxserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, Safari
Data schemeschema-freeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyes, details hereyesyesyes
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.nonononono
Secondary indexesnoyesyes infoalso supports composite index and range indexyesyes
SQL infoSupport of SQLClose to SQL99, but no user access control, stored procedures and host language bindings.SQL-like query language (GQL)noA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersSQL-like query language infovia JavaScript builder pattern
APIs and other access methodsJavaScript APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
TinkerPop Gremlin
JDBC
ODBC
Supported programming languagesJavaScript.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Groovy
Java
Python
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
JavaScript
Server-side scripts infoStored proceduresnousing Google App Engineasynchronous Gremlin script jobsnono
TriggersyesCallbacks using the Google Apps EnginenonoUsing read-only observers
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using Paxosyes infodepending on used storage backend, e.g. Cassandra and HBaseMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowvia hugegraph-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate 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.Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsyes infoedges in graphnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infoonly for local storage and DOM-storageACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infoby using IndexedDB, SQL.JS or proprietary FileStorageyesyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Database
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesnoyes infousing MemoryDB
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users, roles and permissionsrights management via user accountsno

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More resources
AlaSQLGoogle Cloud DatastoreHugeGraphJaguarDBLovefield
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