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DBMS > HarperDB vs. Microsoft Azure Data Explorer vs. Oracle vs. Sphinx vs. Trafodion

System Properties Comparison HarperDB vs. Microsoft Azure Data Explorer vs. Oracle vs. Sphinx vs. Trafodion

Editorial information provided by DB-Engines
NameHarperDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOracle  Xexclude from comparisonSphinx  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Fully managed big data interactive analytics platformWidely used RDBMSOpen source search engine for searching in data from different sources, e.g. relational databasesTransactional SQL-on-Hadoop DBMS
Primary database modelDocument storeRelational DBMS infocolumn orientedRelational DBMSSearch engineRelational 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.60
Rank#244  Overall
#38  Document stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score1244.08
Rank#1  Overall
#1  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitewww.harperdb.ioazure.microsoft.com/­services/­data-explorerwww.oracle.com/­databasesphinxsearch.comtrafodion.apache.org
Technical documentationdocs.harperdb.io/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­en/­databasesphinxsearch.com/­docstrafodion.apache.org/­documentation.html
DeveloperHarperDBMicrosoftOracleSphinx Technologies Inc.Apache Software Foundation, originally developed by HP
Initial release20172019198020012014
Current release3.1, August 2021cloud service with continuous releases23c, September 20233.5.1, February 20232.3.0, February 2019
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercialcommercial inforestricted free version is availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageNode.jsC and C++C++C++, Java
Server operating systemsLinux
OS X
hostedAIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemedynamic schemaFixed schema with schema-less datatypes (dynamic)yes infoSchemaless in JSON and XML columnsyesyes
Typing infopredefined data types such as float or dateyes infoJSON data typesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesnoyes
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.noyesyesno
Secondary indexesyesall fields are automatically indexedyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like data manipulation statementsKusto Query Language (KQL), SQL subsetyes infowith proprietary extensionsSQL-like query language (SphinxQL)yes
APIs and other access methodsJDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary protocolADO.NET
JDBC
ODBC
Supported programming languages.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
.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++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresCustom Functions infosince release 3.1Yes, possible languages: KQL, Python, RPL/SQL infoalso stored procedures in Java possiblenoJava Stored Procedures
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesnono
Partitioning methods infoMethods for storing different data on different nodesA table resides as a whole on one (or more) nodes in a clusterSharding infoImplicit feature of the cloud serviceSharding, horizontal partitioningSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infothe nodes on which a table resides can be definedyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
noneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno infocan be realized in PL/SQLnoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnoACID infoisolation level can be parameterizednoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes, using LMDByesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoVersion 12c introduced the new option 'Oracle Database In-Memory'no
User concepts infoAccess controlAccess rights for users and rolesAzure Active Directory Authenticationfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
HarperDBMicrosoft Azure Data ExplorerOracleSphinxTrafodion
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