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DBMS > Apache Phoenix vs. Google Cloud Datastore vs. NCache vs. Spark SQL

System Properties Comparison Apache Phoenix vs. Google Cloud Datastore vs. NCache vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonNCache  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformOpen-Source and Enterprise in-memory Key-Value StoreSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument storeKey-value storeRelational DBMS
Secondary database modelsDocument store
Search engine infoUsing distributed Lucene
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.96
Rank#195  Overall
#29  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orgcloud.google.com/­datastorewww.alachisoft.com/­ncachespark.apache.org/­sql
Technical documentationphoenix.apache.orgcloud.google.com/­datastore/­docswww.alachisoft.com/­resources/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationGoogleAlachisoftApache Software Foundation
Initial release2014200820052014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20195.3.3, April 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoEnterprise Edition availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC#, .NET, .NET Core, JavaScala
Server operating systemsLinux
Unix
Windows
hostedLinux
Windows
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes, details herepartial infoSupported data types are Lists, Queues, Hashsets, Dictionary and Counteryes
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.nononono
Secondary indexesyesyesyesno
SQL infoSupport of SQLyesSQL-like query language (GQL)SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.SQL-like DML and DDL statements
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
IDistributedCache
JCache
LINQ
Proprietary native API
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsusing Google App Engineno infosupport for stored procedures with SQL-Server CLRno
TriggersnoCallbacks using the Google Apps Engineyes infoNotificationsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyesyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using Paxosyes, with selectable consistency levelnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyes infousing Google Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual 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.Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsoptimistic locking and pessimistic lockingno
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.yesnoyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)no
More information provided by the system vendor
Apache PhoenixGoogle Cloud DatastoreNCacheSpark SQL
Specific characteristicsNCache has been the market leader in .NET Distributed Caching since 2005 . NCache...
» more
Competitive advantagesNCache is 100% .NET/ .NET Core based which fully supports ASP.NET Core Sessions ,...
» more
Typical application scenariosNCache enables industries like retail, finance, banking IoT, travel, ecommerce, healthcare...
» more
Key customersBank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
» more
Market metricsMarket Leader in .NET Distributed Caching since 2005.
» more
Licensing and pricing modelsNCache Open Source is free on an as-is basis without any support. NCache Enterprise...
» more

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More resources
Apache PhoenixGoogle Cloud DatastoreNCacheSpark SQL
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