In-Memory Unterstützung Gibt es Möglichkeiten einige oder alle Strukturen nur im Hauptspeicher zu halten
yes, run db with in-memory only mode
yes (enterprise version only)
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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.
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
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.