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DBMS > Greenplum vs. Hawkular Metrics vs. Microsoft Azure Data Explorer vs. Oracle NoSQL vs. Sadas Engine

System Properties Comparison Greenplum vs. Hawkular Metrics vs. Microsoft Azure Data Explorer vs. Oracle NoSQL vs. Sadas Engine

Editorial information provided by DB-Engines
NameGreenplum  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOracle NoSQL  Xexclude from comparisonSadas Engine  Xexclude from comparison
DescriptionAnalytic 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.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Fully managed big data interactive analytics platformA multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodesSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primary database modelRelational DBMSTime Series DBMSRelational DBMS infocolumn orientedDocument store
Key-value store
Relational DBMS
Relational DBMS
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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.37
Rank#48  Overall
#30  Relational DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score2.95
Rank#100  Overall
#17  Document stores
#17  Key-value stores
#50  Relational DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Websitegreenplum.orgwww.hawkular.orgazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­nosql/­technologies/­nosqlwww.sadasengine.com
Technical documentationdocs.greenplum.orgwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­en/­database/­other-databases/­nosql-database/­index.htmlwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperPivotal Software Inc.Community supported by Red HatMicrosoftOracleSADAS s.r.l.
Initial release20052014201920112006
Current release7.0.0, September 2023cloud service with continuous releases23.3, December 20238.0
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache 2.0commercialOpen Source infoProprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)commercial infofree trial version available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++
Server operating systemsLinuxLinux
OS X
Windows
hostedLinux
Solaris SPARC/x86
AIX
Linux
Windows
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)Support Fixed schema and Schema-less deployment with the ability to interoperate between them.yes
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesoptionalyes
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.yes infosince Version 4.2noyesnono
Secondary indexesyesnoall fields are automatically indexedyesyes
SQL infoSupport of SQLyesnoKusto Query Language (KQL), SQL subsetSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
HTTP RESTMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
Proprietary protocol
Supported programming languagesC
Java
Perl
Python
R
Go
Java
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresyesnoYes, possible languages: KQL, Python, Rnono
Triggersyesyes infovia Hawkular Alertingyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraSharding infoImplicit feature of the cloud serviceShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factor infobased on Cassandrayes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Electable source-replica replication per shard. Support distributed global deployment with Multi-region table featurenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkwith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency infodepending on configuration
Immediate Consistency
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoconfigurable infoACID within a storage node (=shard)
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.nononoyes infooff heap cacheyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAzure Active Directory AuthenticationAccess rights for users and rolesAccess rights for users, groups and roles according to SQL-standard

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More resources
GreenplumHawkular MetricsMicrosoft Azure Data ExplorerOracle NoSQLSadas Engine
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