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DBMS > MarkLogic vs. Microsoft Azure Data Explorer vs. Oracle vs. Tarantool

System Properties Comparison MarkLogic vs. Microsoft Azure Data Explorer vs. Oracle vs. Tarantool

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Editorial information provided by DB-Engines
NameMarkLogic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOracle  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionOperational and transactional Enterprise NoSQL databaseFully managed big data interactive analytics platformWidely used RDBMSIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS infocolumn orientedRelational DBMSDocument store
Key-value store
Relational DBMS
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
Document store
Graph DBMS infowith Oracle Spatial and Graph
RDF store infowith Oracle Spatial and Graph
Spatial DBMS infowith Oracle Spatial and Graph
Vector DBMS infosince Oracle 23
Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score1244.08
Rank#1  Overall
#1  Relational DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websitewww.progress.com/­marklogicazure.microsoft.com/­services/­data-explorerwww.oracle.com/­databasewww.tarantool.io
Technical documentationwww.progress.com/­marklogic/­documentationdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­en/­databasewww.tarantool.io/­en/­doc
DeveloperMarkLogic Corp.MicrosoftOracleVK
Initial release2001201919802008
Current release11.0, December 2022cloud service with continuous releases23c, September 20232.10.0, May 2022
License infoCommercial or Open Sourcecommercial inforestricted free version is availablecommercialcommercial inforestricted free version is availableOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
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 languageC++C and C++C and C++
Server operating systemsLinux
OS X
Windows
hostedAIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS
BSD
Linux
macOS
Data schemeschema-free infoSchema can be enforcedFixed schema with schema-less datatypes (dynamic)yes infoSchemaless in JSON and XML columnsFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesstring, double, decimal, uuid, integer, blob, boolean, datetime
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.yesyesyesno
Secondary indexesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLyes infoSQL92Kusto Query Language (KQL), SQL subsetyes infowith proprietary extensionsFull-featured ANSI SQL support
APIs and other access methodsJava API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Open binary protocol
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresyes infovia XQuery or JavaScriptYes, possible languages: KQL, Python, RPL/SQL infoalso stored procedures in Java possibleLua, C and SQL stored procedures
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceSharding, horizontal partitioningSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno infocan be realized in PL/SQL
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infocan act as a resource manager in an XA/JTA transactionnoACID infoisolation level can be parameterizedACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, with Range Indexesnoyes infoVersion 12c introduced the new option 'Oracle Database In-Memory'yes, full featured in-memory storage engine with persistence
User concepts infoAccess controlRole-based access control at the document and subdocument levelsAzure Active Directory Authenticationfine grained access rights according to SQL-standardAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources
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Conferences, events and webinars

Oracle Cloud World
Las Vegas, 9-12 September 2024

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