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DBMS > Bangdb

Bangdb Systemeigenschaften

Bitte wählen Sie ein weiteres System aus, um es mit Bangdb zu vergleichen.

Unsere Besucher vergleichen Bangdb oft mit Sphinx, Cassandra und MongoDB.

Redaktionelle Informationen bereitgestellt von DB-Engines
KurzbeschreibungConverged and high performance database for device data, events, time series, document and graph
Primäres DatenbankmodellDocument Store
Graph DBMS
Time Series DBMS
Sekundäre DatenbankmodelleSpatial DBMS
DB-Engines Ranking infomisst die Popularität von Datenbankmanagement- systemenranking trend
Trend Chart
Rang#332  Overall
#45  Document Stores
#34  Graph DBMS
#29  Time Series DBMS
Technische Dokumentationbangdb.com/­developer
EntwicklerSachin Sinha, BangDB
Aktuelle VersionBangDB 2.0, October 2021
Lizenz infoCommercial or Open SourceOpen Source infoBSD 3
Ausschließlich ein Cloud-Service infoNur als Cloud-Service verfügbarnein
DBaaS Angebote (gesponserte Links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
ImplementierungsspracheC, C++
Server BetriebssystemeLinux
Typisierung infovordefinierte Datentypen, z.B. float oder dateyes: string, long, double, int, geospatial, stream, events
XML Unterstützung infoVerarbeitung von Daten in XML Format, beispielsweise Speicherung von XML-Strukturen und/oder Unterstützung von XPath, XQuery, XSLTnein
Sekundärindizesja infosecondary, composite, nested, reverse, geospatial
SQL infoSupport of SQLSQL like support with command line tool
APIs und andere ZugriffskonzeptePropriätäres Protokoll
Unterstützte ProgrammiersprachenC
Server-seitige Scripts infoStored Proceduresnein
Triggersyes, Notifications (with Streaming only)
Partitionierungsmechanismen infoMethoden zum Speichern von unterschiedlichen Daten auf unterschiedlichen KnotenSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm
Replikationsmechanismen infoMethoden zum redundanten Speichern von Daten auf mehreren Knotenselectable replication factor, Knob for CAP (enterprise version only)
MapReduce infoBietet ein API für Map/Reduce Operationennein
Konsistenzkonzept infoMethoden zur Sicherstellung der Konsistenz in einem verteilten SystemTunable consistency, set CAP knob accordingly
Fremdschlüssel inforeferenzielle Integritätnein
Transaktionskonzept infoUnterstützung zur Sicherstellung der Datenintegrität bei nicht-atomaren DatenmanipulationenACID
Concurrency infoUnterstützung von gleichzeitig ausgeführten Datenmanipulationenyes, optimistic concurrency control
Durability infoDauerhafte Speicherung der Datenyes, implements WAL (Write ahead log) as well
In-Memory Unterstützung infoGibt es Möglichkeiten einige oder alle Strukturen nur im Hauptspeicher zu haltenyes, run db with in-memory only mode
Berechtigungskonzept infoZugriffskontrolleyes (enterprise version only)
Weitere Informationen bereitgestellt vom Systemhersteller
Specific characteristics

BangDB is a converged NoSql database platform which natively integrated streaming, AI, Graph and multi model support for predictive data processing in real time. The database is designed and developed to align with the ongoing and future data trend which requires different features and capabilities to be converged within the database.
BangDB is one of the highest performing database in the market. BangDB can get into devices in embedded mode and on local or cloud in distributed mode in interconnected manner. Following are highlights of the database.
Stream processing enables continuous data ingestion and processing for real time predictive analytics.
• Complex event processing enables you to perform state-based, complex data pattern extraction from raw streaming data in real time to discover anomalies, security threats, fraud, or opportunities and take appropriate actions.
• BangDB provides a high capacity, intelligent, and low footprint data ETL agent.
• Integrated AI provides machine learning mechanisms for model training, testing, deployment, prediction, and measurement.
• BangDB works as a graph store, and you can use Cypher to interact with your graphs for such tasks as root cause analysis.
• BangDB supports REST APIs, which you can use for data visualisation with Grafana.
• The BangDB interactive command line interface (CLI) enables you to interact with the database in an easy and efficient manner. You can complete almost all tasks by using the CLI.
• BangDB supports full ACID transactions.
• You can create multiple indexes on structured or non-structured data for quick and efficient access.
• BangDB performs 2X+ better than most other popular NoSQL databases.

Competitive advantages

Converged Platform to break silos for higher scale and performance

BangDB is a novel converged platform which natively integrates AI (ML, IE and DL), Streaming and multi model support to allow developer to enable modern use cases in simple and accelerated manner. BangDB breaks many different silos by integrating different dimensions into a single space. This allows scaling and management of the system efficient and simple. It also allows developers to automate ML operations such as training model, deploying and monitoring and predicting on streaming data.

Real time processing for continuous intelligence and action

BangDB implements integrated streaming capabilties with running statistics for continuous intelligence extraction, finding anomalies and patterns using complex event processing and takes automated actions as configured. Further it implements sliding window for scalable time-series data/event processing. Users can enable end to end scenarios in a simple manner using a config file to ingest high speed unstructured data, process the data and take action as required in automated manner.

Integrated AI for predictive analysis and auto ML ops

AI has become important element for all kinds of data processing. Having AI natively integrated within the db enables user to deal with machine learning activities without exporting data to other silo. This makes the ML operations lot more simple, faster and automated to large extent. BangDB provides simple abstractions to deal with training, deployment and prediction. Further it also allows users to bring their own code or models to the system for any external framework like Tensorflow or python based framework.

Hybrid deployment, multi-model data processing

BangDB can be embedded within devices at edge level for hyper local use cases and then can be connected with local cluster and/or cloud deployment for end to end IOT related use cases processing. This improves data processing speed and efficiency at edge level and optimises the amount of data sent over the network to db cluster. The multi model data processing support all kinds of data to be ingested within the database without having to structure upfront. Further, graph processing both in explicit and implicit manner allows root cause analysis using ontologies as natural part of the system

SSD for higher performance for large data with cost efficiency

BangDB implements IO Layer which treats SSDs as extension of virtual memory rather than replacement of file system. This allows database to handle lot more data than available memory with high performance. This also brings the flexibility in handling large volume of data at scale with cost efficiency. 

Typical application scenarios

IOT and time series data monitoring

Devops, servers, network monitoring

Real-Time analytics, anomaly and pattern detection

Personalisation, reccommendation

Connected vehicles and personal assistance

Key customers

Cisco, Accenture, Opera, Airpay, CtrlS, makemytrip, wine central, over 150 SaaS customers

Market metrics

BangDB is one of the fastest databases in the marke with over 2X performance over others. BangDB has over 100,000 subscriptions for many different use cases especially in the IOT and emerging data scenarios.

Licensing and pricing models

BangDB community and enterprise model. Details at https://bangdb.com/pricing/

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