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DBMS > Bangdb vs. HarperDB vs. Microsoft Azure Data Explorer vs. Teradata vs. Virtuoso

System Properties Comparison Bangdb vs. HarperDB vs. Microsoft Azure Data Explorer vs. Teradata vs. Virtuoso

Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonHarperDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTeradata  Xexclude from comparisonVirtuoso  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphUltra-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 platformA hybrid cloud data analytics software platform (Teradata Vantage)Virtuoso is a multi-model hybrid-RDBMS that supports management of data represented as relational tables and/or property graphs
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Document storeRelational DBMS infocolumn orientedRelational DBMSDocument store
Graph DBMS
Native XML DBMS
Relational DBMS
RDF store
Search engine
Secondary database modelsSpatial DBMSDocument 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
Spatial DBMS
Time Series DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score0.55
Rank#248  Overall
#38  Document stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Score4.26
Rank#78  Overall
#13  Document stores
#4  Graph DBMS
#2  Native XML DBMS
#42  Relational DBMS
#2  RDF stores
#9  Search engines
Websitebangdb.comwww.harperdb.ioazure.microsoft.com/­services/­data-explorerwww.teradata.comvirtuoso.openlinksw.com
Technical documentationdocs.bangdb.comdocs.harperdb.io/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.teradata.comdocs.openlinksw.com/­virtuoso
DeveloperSachin Sinha, BangDBHarperDBMicrosoftTeradataOpenLink Software
Initial release20122017201919841998
Current releaseBangDB 2.0, October 20213.1, August 2021cloud service with continuous releasesTeradata Vantage 1.0 MU2, January 20197.2.11, September 2023
License infoCommercial or Open SourceOpen Source infoBSD 3commercial infofree community edition availablecommercialcommercialOpen Source infoGPLv2, extended commercial 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 languageC, C++Node.jsC
Server operating systemsLinuxLinux
OS X
hostedhosted
Linux
AIX
FreeBSD
HP-UX
Linux
OS X
Solaris
Windows
Data schemeschema-freedynamic schemaFixed schema with schema-less datatypes (dynamic)yesyes infoSQL - Standard relational schema
RDF - Quad (S, P, O, G) or Triple (S, P, O)
XML - DTD, XML Schema
DAV - freeform filesystem objects, plus User Defined Types a/k/a Dynamic Extension Type
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyes infoJSON data typesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes
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.nonoyesyesyes
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesall fields are automatically indexedyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash indexyes
SQL infoSupport of SQLSQL like support with command line toolSQL-like data manipulation statementsKusto Query Language (KQL), SQL subsetyes infoSQL 2016 + extensionsyes infoSQL-92, SQL-200x, SQL-3, SQLX
APIs and other access methodsProprietary protocol
RESTful HTTP API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
ADO.NET
GeoSPARQL
HTTP API
JDBC
Jena RDF API
ODBC
OLE DB
RDF4J API
RESTful HTTP API
Sesame REST HTTP Protocol
SOAP webservices
SPARQL 1.1
WebDAV
XPath
XQuery
XSLT
Supported programming languagesC
C#
C++
Java
Python
.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++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
.Net
C
C#
C++
Java
JavaScript
Perl
PHP
Python
Ruby
Visual Basic
Server-side scripts infoStored proceduresnoCustom Functions infosince release 3.1Yes, possible languages: KQL, Python, Ryes infoUDFs, stored procedures, table functions in parallelyes infoVirtuoso PL
Triggersyes, Notifications (with Streaming only)noyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmA table resides as a whole on one (or more) nodes in a clusterSharding infoImplicit feature of the cloud serviceSharding infoHashingyes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)yes 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
Chain, star, and bi-directional replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyes, using LMDByesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, run db with in-memory only modeyesnoyesyes
User concepts infoAccess controlyes (enterprise version only)Access rights for users and rolesAzure Active Directory Authenticationfine grained access rights according to SQL-standardFine-grained Attribute-Based Access Control (ABAC) in addition to typical coarse-grained Role-Based Access Control (RBAC) according to SQL-standard. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)
More information provided by the system vendor
BangdbHarperDBMicrosoft Azure Data ExplorerTeradataVirtuoso
Specific characteristicsVirtuoso is a modern multi-model RDBMS for managing data represented as tabular relations...
» more
Competitive advantagesPerformance & Scale — as exemplified by DBpedia and the LOD Cloud it spawned, i.e.,...
» more
Typical application scenariosUsed for — Analytics/BI Conceptual Data Virtualization Enterprise Knowledge Graphs...
» more
Key customersBroad use across enterprises and governments including — European Union (EU) US Government...
» more
Market metricsLargest installed-base ​of Multi-Model RDBMS for AI-friendly Knowledge Graphs Platform...
» more
Licensing and pricing modelsAvailable in both Commercial Enterprise and Open Source (GPL v2) Editions Feature...
» more

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BangdbHarperDBMicrosoft Azure Data ExplorerTeradataVirtuoso
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