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DBMS > Apache Phoenix vs. Google Cloud Bigtable vs. InfinityDB vs. PostGIS

System Properties Comparison Apache Phoenix vs. Google Cloud Bigtable vs. InfinityDB vs. PostGIS

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonInfinityDB  Xexclude from comparisonPostGIS  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A Java embedded Key-Value Store which extends the Java Map interfaceSpatial extension of PostgreSQL
Primary database modelRelational DBMSKey-value store
Wide column store
Key-value storeSpatial DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.00
Rank#378  Overall
#57  Key-value stores
Score22.69
Rank#29  Overall
#1  Spatial DBMS
Websitephoenix.apache.orgcloud.google.com/­bigtableboilerbay.compostgis.net
Technical documentationphoenix.apache.orgcloud.google.com/­bigtable/­docsboilerbay.com/­infinitydb/­manualpostgis.net/­documentation
DeveloperApache Software FoundationGoogleBoiler Bay Inc.
Initial release2014201520022005
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20194.03.4.2, February 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoGPL v2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC
Server operating systemsLinux
Unix
Windows
hostedAll OS with a Java VM
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyes
Typing infopredefined data types such as float or dateyesnoyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes
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.nononoyes
Secondary indexesyesnono infomanual creation possible, using inversions based on multi-value capabilityyes
SQL infoSupport of SQLyesnonoyes
APIs and other access methodsJDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
Java
Server-side scripts infoStored proceduresuser defined functionsnonouser defined functions
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneyes infobased on PostgreSQL
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Internal replication in Colossus, and regional replication between two clusters in different zonesnoneyes infobased on PostgreSQL
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate Consistency
Foreign keys infoReferential integritynonono infomanual creation possible, using inversions based on multi-value capabilityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACID infoOptimistic locking for transactions; no isolation for bulk loadsACID
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.yesnonono
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)noyes infobased on PostgreSQL

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More resources
Apache PhoenixGoogle Cloud BigtableInfinityDBPostGIS
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Recent citations in the news

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services
2 June 2016, AWS Blog

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