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DBMS > AgensGraph vs. Drizzle vs. Microsoft Azure Data Explorer vs. Netezza vs. Oracle Berkeley DB

System Properties Comparison AgensGraph vs. Drizzle vs. Microsoft Azure Data Explorer vs. Netezza vs. Oracle Berkeley DB

Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonDrizzle  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Fully managed big data interactive analytics platformData warehouse and analytics appliance part of IBM PureSystemsWidely used in-process key-value store
Primary database modelGraph DBMS
Relational DBMS
Relational DBMSRelational DBMS infocolumn orientedRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Secondary database modelsDocument 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
Score0.23
Rank#315  Overall
#26  Graph DBMS
#140  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Websitebitnine.net/­agensgraphazure.microsoft.com/­services/­data-explorerwww.ibm.com/­products/­netezzawww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationbitnine.net/­documentationdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperBitnine Global Inc.Drizzle project, originally started by Brian AkerMicrosoftIBMOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release20162008201920001994
Current release2.1, December 20187.2.4, September 2012cloud service with continuous releases18.1.40, May 2020
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoGNU GPLcommercialcommercialOpen Source infocommercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++C, Java, C++ (depending on the Berkeley DB edition)
Server operating systemsLinux
OS X
Windows
FreeBSD
Linux
OS X
hostedLinux infoincluded in applianceAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemedepending on used data modelyesFixed schema with schema-less datatypes (dynamic)yesschema-free
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-typesyesno
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.noyesyes infoonly with the Berkeley DB XML edition
Secondary indexesyesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLyesyes infowith proprietary extensionsKusto Query Language (KQL), SQL subsetyesyes infoSQL interfaced based on SQLite is available
APIs and other access methodsCypher Query Language
JDBC
JDBCMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
OLE DB
Supported programming languagesC
Java
JavaScript
Python
C
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Server-side scripts infoStored proceduresyesnoYes, possible languages: KQL, Python, Ryesno
Triggersnono infohooks for callbacks inside the server can be used.yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceShardingSharding infoImplicit feature of the cloud serviceShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardPluggable authentication mechanisms infoe.g. LDAP, HTTPAzure Active Directory AuthenticationUsers with fine-grained authorization conceptno

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More resources
AgensGraphDrizzleMicrosoft Azure Data ExplorerNetezza infoAlso called PureData System for Analytics by IBMOracle Berkeley DB
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