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DBMS > Apache Phoenix vs. Geode vs. Greenplum vs. Microsoft Azure Data Explorer vs. SWC-DB

System Properties Comparison Apache Phoenix vs. Geode vs. Greenplum vs. Microsoft Azure Data Explorer vs. SWC-DB

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGeode  Xexclude from comparisonGreenplum  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.Fully managed big data interactive analytics platformA high performance, scalable Wide Column DBMS
Primary database modelRelational DBMSKey-value storeRelational DBMSRelational DBMS infocolumn orientedWide column store
Secondary database modelsDocument store
Spatial DBMS
Document store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score1.86
Rank#134  Overall
#24  Key-value stores
Score8.08
Rank#48  Overall
#31  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.08
Rank#364  Overall
#13  Wide column stores
Websitephoenix.apache.orggeode.apache.orggreenplum.orgazure.microsoft.com/­services/­data-explorergithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationphoenix.apache.orggeode.apache.org/­docsdocs.greenplum.orgdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software FoundationOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.Pivotal Software Inc.MicrosoftAlex Kashirin
Initial release20142002200520192020
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20191.1, February 20177.0.0, September 2023cloud service with continuous releases0.5, April 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses available as GemfireOpen Source infoApache 2.0commercialOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++
Server operating systemsLinux
Unix
Windows
All OS with a Java VM infothe JDK (8 or later) is also requiredLinuxhostedLinux
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.nonoyes infosince Version 4.2yesno
Secondary indexesyesnoyesall fields are automatically indexed
SQL infoSupport of SQLyesSQL-like query language (OQL)yesKusto Query Language (KQL), SQL subsetSQL-like query language
APIs and other access methodsJDBCJava Client API
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary protocol
Thrift
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
All JVM based languages
C++
Groovy
Java
Scala
C
Java
Perl
Python
R
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsyesYes, possible languages: KQL, Python, Rno
Triggersnoyes infoCache Event Listenersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replicationSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes, on a single nodeACIDno
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.yesyesnonono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights per client and object definablefine grained access rights according to SQL-standardAzure Active Directory Authentication

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More resources
Apache PhoenixGeodeGreenplumMicrosoft Azure Data ExplorerSWC-DB infoSuper Wide Column Database
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