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DBMS > Apache Phoenix vs. Atos Standard Common Repository vs. DuckDB vs. Google Cloud Spanner

System Properties Comparison Apache Phoenix vs. Atos Standard Common Repository vs. DuckDB vs. Google Cloud Spanner

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonDuckDB  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksAn embeddable, in-process, column-oriented SQL OLAP RDBMSA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.
Primary database modelRelational DBMSDocument store
Key-value store
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score4.63
Rank#69  Overall
#37  Relational DBMS
Score2.84
Rank#100  Overall
#51  Relational DBMS
Websitephoenix.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositoryduckdb.orgcloud.google.com/­spanner
Technical documentationphoenix.apache.orgduckdb.org/­docscloud.google.com/­spanner/­docs
DeveloperApache Software FoundationAtos Convergence CreatorsGoogle
Initial release2014201620182017
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 201917031.0.0, June 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoMIT Licensecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC++
Server operating systemsLinux
Unix
Windows
Linuxserver-lesshosted
Data schemeyes infolate-bound, schema-on-read capabilitiesSchema and schema-less with LDAP viewsyesyes
Typing infopredefined data types such as float or dateyesoptionalyesyes
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.noyesnono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesnoyesyes infoQuery statements complying to ANSI 2011
APIs and other access methodsJDBCLDAPArrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
All languages with LDAP bindingsC
C# info3rd party driver
C++
Crystal info3rd party driver
Go info3rd party driver
Java
Lisp info3rd party driver
Python
R
Ruby info3rd party driver
Rust
Swift
Zig info3rd party driver
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functionsnonono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infocell divisionnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesnoneMulti-source replication with 3 replicas for regional instances.
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrity
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsACIDACID infoStrict serializable isolation
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
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.yesyesyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyLDAP bind authenticationnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Apache PhoenixAtos Standard Common RepositoryDuckDBGoogle Cloud Spanner
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Recent citations in the news

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services
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