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DBMS > Apache Phoenix vs. Fauna vs. GigaSpaces vs. Spark SQL vs. Teradata Aster

System Properties Comparison Apache Phoenix vs. Fauna vs. GigaSpaces vs. Spark SQL vs. Teradata Aster

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonGigaSpaces  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseFauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsSpark SQL is a component on top of 'Spark Core' for structured data processingPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSDocument store
Graph DBMS
Relational DBMS
Time Series DBMS
Document store
Object oriented DBMS infoValues are user defined objects
Relational DBMSRelational DBMS
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score1.52
Rank#153  Overall
#26  Document stores
#14  Graph DBMS
#71  Relational DBMS
#13  Time Series DBMS
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orgfauna.comwww.gigaspaces.comspark.apache.org/­sql
Technical documentationphoenix.apache.orgdocs.fauna.comdocs.gigaspaces.com/­latest/­landing.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationFauna, Inc.Gigaspaces TechnologiesApache Software FoundationTeradata
Initial release20142014200020142005
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 201915.5, September 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaJava, C++, .NetScala
Server operating systemsLinux
Unix
Windows
hostedLinux
macOS
Solaris
Windows
Linux
OS X
Windows
Linux
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeschema-freeyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesnoyesyesyes
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 infoXML can be used for describing objects metadatanoyes infoin Aster File Store
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLyesnoSQL-99 for query and DML statementsSQL-like DML and DDL statementsyes
APIs and other access methodsJDBCRESTful HTTP APIGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
.Net
C++
Java
Python
Scala
Java
Python
R
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsyesnoR packages
Triggersnonoyes, event driven architecturenono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoconsistent hashingShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replicationMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
noneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoyes infoMap-Reduce pattern can be built with XAP task executorsyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesnono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyIdentity management, authentication, and access controlRole-based access controlnofine grained access rights according to SQL-standard

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More resources
Apache PhoenixFauna infopreviously named FaunaDBGigaSpacesSpark SQLTeradata Aster
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