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DBMS > HarperDB vs. Microsoft Azure Data Explorer vs. UniData,UniVerse vs. Vertica

System Properties Comparison HarperDB vs. Microsoft Azure Data Explorer vs. UniData,UniVerse vs. Vertica

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Editorial information provided by DB-Engines
NameHarperDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonUniData,UniVerse  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
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 platformMultiValue database and application server with SQL mapping layer and meta database capabilitiesCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelDocument storeRelational DBMS infocolumn orientedMultivalue DBMSRelational DBMS infoColumn oriented
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
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.55
Rank#248  Overall
#38  Document stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score3.16
Rank#97  Overall
#2  Multivalue DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitewww.harperdb.ioazure.microsoft.com/­services/­data-explorerwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-unidatawww.vertica.com
Technical documentationdocs.harperdb.io/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.rocketsoftware.com/­bundle?cluster=true&labelkey=unidata&labelkey=prod_unidatavertica.com/­documentation
DeveloperHarperDBMicrosoftRocket SoftwareOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2017201919852005
Current release3.1, August 2021cloud service with continuous releases12.0.3, January 2023
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercialcommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenoyesnono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageNode.jsCC++
Server operating systemsLinux
OS X
hostedAIX
HP-UX
Linux
Solaris
Windows
Linux
Data schemedynamic schemaFixed schema with schema-less datatypes (dynamic)schema-freeYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
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-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.noyesno
Secondary indexesyesall fields are automatically indexedyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like data manipulation statementsKusto Query Language (KQL), SQL subsetyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Java API infoJPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
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
.Net
Basic infoU2 Basic
C
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresCustom Functions infosince release 3.1Yes, possible languages: KQL, Python, Ryesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoU2 Basicyes, called Custom Alerts
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 servicenonehorizontal partitioning, hierarchical partitioning
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.Source-replica replicationMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnoACID infoconfigurableACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes, using LMDByesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlAccess rights for users and rolesAzure Active Directory AuthenticationAccess rights according to SQL-standard and operating system basedfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
HarperDBMicrosoft Azure Data ExplorerUniData,UniVerseVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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HarperDBMicrosoft Azure Data ExplorerUniData,UniVerseVertica infoOpenText™ Vertica™
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