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Bangdb System Properties

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Editorial information provided by DB-Engines
DescriptionConverged and high performance database for device data, events, time series, document and graph
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Rank#332  Overall
#45  Document stores
#34  Graph DBMS
#29  Time Series DBMS
Technical documentationbangdb.com/­developer
DeveloperSachin Sinha, BangDB
Initial release2012
Current releaseBangDB 2.0, October 2021
License infoCommercial or Open SourceOpen Source infoBSD 3
Cloud-based only infoOnly available as a cloud serviceno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++
Server operating systemsLinux
Data schemeschema-free
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, events
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.no
Secondary indexesyes infosecondary, composite, nested, reverse, geospatial
SQL infoSupport of SQLSQL like support with command line tool
APIs and other access methodsProprietary protocol
Supported programming languagesC
Server-side scripts infoStored proceduresno
Triggersyes, Notifications (with Streaming only)
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordingly
Foreign keys infoReferential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency control
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as well
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 mode
User concepts infoAccess controlyes (enterprise version only)
More information provided by the system vendor
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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