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DBMS > Apache Phoenix vs. Databricks vs. InfinityDB vs. InfluxDB

System Properties Comparison Apache Phoenix vs. Databricks vs. InfinityDB vs. InfluxDB

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDatabricks  Xexclude from comparisonInfinityDB  Xexclude from comparisonInfluxDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A Java embedded Key-Value Store which extends the Java Map interfaceDBMS for storing time series, events and metrics
Primary database modelRelational DBMSDocument store
Relational DBMS
Key-value storeTime Series DBMS
Secondary database modelsSpatial DBMS infowith GEO package
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.00
Rank#378  Overall
#57  Key-value stores
Score25.83
Rank#28  Overall
#1  Time Series DBMS
Websitephoenix.apache.orgwww.databricks.comboilerbay.comwww.influxdata.com/­products/­influxdb-overview
Technical documentationphoenix.apache.orgdocs.databricks.comboilerbay.com/­infinitydb/­manualdocs.influxdata.com/­influxdb
DeveloperApache Software FoundationDatabricksBoiler Bay Inc.
Initial release2014201320022013
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20194.02.7.6, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoMIT-License; commercial enterprise version available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaGo
Server operating systemsLinux
Unix
Windows
hostedAll OS with a Java VMLinux
OS X infothrough Homebrew
Data schemeyes infolate-bound, schema-on-read capabilitiesFlexible Schema (defined schema, partial schema, schema free)yes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeschema-free
Typing infopredefined data types such as float or dateyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysNumeric data and Strings
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 indexesyesyesno infomanual creation possible, using inversions based on multi-value capabilityno
SQL infoSupport of SQLyeswith Databricks SQLnoSQL-like query language
APIs and other access methodsJDBCJDBC
ODBC
RESTful HTTP API
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
HTTP API
JSON over UDP
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Python
R
Scala
Java.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
Server-side scripts infoStored proceduresuser defined functionsuser defined functions and aggregatesnono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoin enterprise version only
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesnoneselectable replication factor infoin enterprise version only
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZED
Foreign keys infoReferential integritynono infomanual creation possible, using inversions based on multi-value capabilityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsno
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.yesnonoyes infoDepending on used storage engine
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynosimple rights management via user accounts
More information provided by the system vendor
Apache PhoenixDatabricksInfinityDBInfluxDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
InfluxData is the creator of InfluxDB , the open source time series database. It...
» more
Competitive advantagesTime to Value InfluxDB is available in all the popular languages and frameworks,...
» more
Typical application scenariosIoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more
Key customersInfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more
Market metricsFastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more
Licensing and pricing modelsOpen source core with closed source clustering available either on-premise or on...
» more
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