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DBMS > Apache Phoenix vs. Databricks vs. GridDB vs. Informix

System Properties Comparison Apache Phoenix vs. Databricks vs. GridDB vs. Informix

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDatabricks  Xexclude from comparisonGridDB  Xexclude from comparisonInformix  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.Scalable in-memory time series database optimized for IoT and Big DataA secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things data
Primary database modelRelational DBMSDocument store
Relational DBMS
Time Series DBMSRelational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDB
Secondary database modelsKey-value store
Relational DBMS
Document store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
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
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score17.87
Rank#35  Overall
#22  Relational DBMS
Websitephoenix.apache.orgwww.databricks.comgriddb.netwww.ibm.com/­products/­informix
Technical documentationphoenix.apache.orgdocs.databricks.comdocs.griddb.netinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
DeveloperApache Software FoundationDatabricksToshiba CorporationIBM, HCL Technologies infoEffective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.
Initial release2014201320131984
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20195.1, August 202214.10.FC5, November 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C, C++ and Java
Server operating systemsLinux
Unix
Windows
hostedLinuxAIX
HP-UX
Linux
macOS
Solaris
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyes infoSince Version 12.10 support for JSON/BSON datatypes
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.noyesno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyeswith Databricks SQLSQL92, SQL-like TQL (Toshiba Query Language)yes
APIs and other access methodsJDBCJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Python
R
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsuser defined functions and aggregatesnoyes
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID at container levelACID
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.yesnoyesyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users can be defined per databaseUsers with fine-grained authentication, authorization, and auditing controls
More information provided by the system vendor
Apache PhoenixDatabricksGridDBInformix
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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Apache PhoenixDatabricksGridDBInformix
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