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DBMS > AlaSQL vs. Google Cloud Datastore vs. Hypertable vs. RavenDB vs. TigerGraph

System Properties Comparison AlaSQL vs. Google Cloud Datastore vs. Hypertable vs. RavenDB vs. TigerGraph

Editorial information provided by DB-Engines
NameAlaSQL  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHypertable  Xexclude from comparisonRavenDB  Xexclude from comparisonTigerGraph  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionJavaScript DBMS libraryAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAn open source BigTable implementation based on distributed file systems such as HadoopOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelDocument store
Relational DBMS
Document storeWide column storeDocument storeGraph DBMS
Secondary database modelsGraph DBMS
Spatial 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
Score4.47
Rank#76  Overall
#12  Document stores
Score2.92
Rank#101  Overall
#18  Document stores
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websitealasql.orgcloud.google.com/­datastoreravendb.netwww.tigergraph.com
Technical documentationgithub.com/­AlaSQL/­alasqlcloud.google.com/­datastore/­docsravendb.net/­docsdocs.tigergraph.com
DeveloperAndrey Gershun & Mathias R. WulffGoogleHypertable Inc.Hibernating Rhinos
Initial release20142008200920102017
Current release0.9.8.11, March 20165.4, July 2022
License infoCommercial or Open SourceOpen Source infoMIT-LicensecommercialOpen Source infoGNU version 3. Commercial license availableOpen Source infoAGPL version 3, commercial license availablecommercial
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 languageJavaScriptC++C#C++
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)hostedLinux
OS X
Windows infoan inofficial Windows port is available
Linux
macOS
Raspberry Pi
Windows
Linux
Data schemeschema-freeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or datenoyes, details herenonoyes
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.nonono
Secondary indexesnoyesrestricted infoonly exact value or prefix value scansyes
SQL infoSupport of SQLClose to SQL99, but no user access control, stored procedures and host language bindings.SQL-like query language (GQL)noSQL-like query language (RQL)SQL-like query language (GSQL)
APIs and other access methodsJavaScript APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
C++ 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
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesJavaScript.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
Perl
PHP
Python
Ruby
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
Server-side scripts infoStored proceduresnousing Google App Enginenoyesyes
TriggersyesCallbacks using the Google Apps Enginenoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using Paxosselectable replication factor on file system levelMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyesyesyes
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.Immediate 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 integrityyesyes infovia ReferenceProperties or Ancestor pathsnonoyes infoRelationships in graphs
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 TransactionsnoACID, Cluster-wide transaction availableACID
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.yesnono
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAuthorization levels configured per client per databaseRole-based access control

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More resources
AlaSQLGoogle Cloud DatastoreHypertableRavenDBTigerGraph
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