> For the complete documentation index, see [llms.txt](https://docs.fractalworks.io/joule/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.fractalworks.io/joule/components.md).

# Components

- [Pipelines](https://docs.fractalworks.io/joule/components/pipelines.md): Data (stream) pipelines enable business-specific, real-time analytics use cases
- [Use case anatomy](https://docs.fractalworks.io/joule/components/pipelines/use-case-anatomy.md): A use case binds together the required data and stream pipeline unit to perform the desired function
- [Data priming](https://docs.fractalworks.io/joule/components/pipelines/data-priming.md): Prime Joule with necessary startup data
- [Types of import](https://docs.fractalworks.io/joule/components/pipelines/data-priming/types-of-import.md): Parquet and CSV data imports for stream processing
- [Processing unit](https://docs.fractalworks.io/joule/components/pipelines/processing-unit.md): Quickly build custom business use cases
- [Group by](https://docs.fractalworks.io/joule/components/pipelines/group-by.md): Groups events by attributes to drive optimised computation functions
- [Emit computed events](https://docs.fractalworks.io/joule/components/pipelines/emit-computed-events.md): Select and filter output events for publishing
- [Telemetry auditing](https://docs.fractalworks.io/joule/components/pipelines/telemetry-auditing.md): Audit and track events for validation and testing
- [Processors](https://docs.fractalworks.io/joule/components/processors.md): Processors are the core of the Joule platform, each performing a specific task. These create use case when linked together
- [Common attributes](https://docs.fractalworks.io/joule/components/processors/common-attributes.md): Core processor attributes that provide out-of-the-box features
- [Filters](https://docs.fractalworks.io/joule/components/processors/filters.md): Reduce stream processing overhead by filtering irrelevant events
- [By type](https://docs.fractalworks.io/joule/components/processors/filters/by-type.md): Filter events based on specific types from the processing pipeline
- [By expression](https://docs.fractalworks.io/joule/components/processors/filters/by-expression.md): Use Javascript expressions to define custom filters
- [Send on delta](https://docs.fractalworks.io/joule/components/processors/filters/send-on-delta.md): Stateful filter processor that filters previous seen events
- [Remove attributes](https://docs.fractalworks.io/joule/components/processors/filters/remove-attributes.md): Remove sensitive attributes from an event
- [Drop all events](https://docs.fractalworks.io/joule/components/processors/filters/drop-all-events.md): Drop all incoming events in the processor
- [Enrichment](https://docs.fractalworks.io/joule/components/processors/enrichment.md): Enrich events using connected contextual data, metrics and analytics
- [Key concepts](https://docs.fractalworks.io/joule/components/processors/enrichment/key-concepts.md): Enriching events with the latest contextual data is crucial for processing advanced real-time business insights
- [Anatomy of enrichment DSL](https://docs.fractalworks.io/joule/components/processors/enrichment/key-concepts/anatomy-of-enrichment-dsl.md): The enrichment DSL provides a flexible syntax that enables the user to define field level enrichments
- [Banking example](https://docs.fractalworks.io/joule/components/processors/enrichment/key-concepts/banking-example.md): The below banking example enriches events using the linked contextual data and metrics
- [Enrichment catalogue](https://docs.fractalworks.io/joule/components/processors/enrichment/key-concepts/enrichment-catalogue.md)
- [Old version of Key concepts](https://docs.fractalworks.io/joule/components/processors/enrichment/old-version-of-key-concepts.md): Enriching event data with the latest contextual data is crucial for processing real-time business insights.
- [Metrics](https://docs.fractalworks.io/joule/components/processors/enrichment/metrics.md): Enrich events with pre-calculated metrics to facilitate further advanced processing
- [Dynamic contextual data](https://docs.fractalworks.io/joule/components/processors/enrichment/dynamic-contextual-data.md): Use fast, connected data stores to quickly enrich in-motion events with up-to-date context
- [Caching architecture](https://docs.fractalworks.io/joule/components/processors/enrichment/dynamic-contextual-data/caching-architecture.md): Caching is a key enabler for low-latency contextual data access
- [Static contextual data](https://docs.fractalworks.io/joule/components/processors/enrichment/static-contextual-data.md): Enrich events with essential slow changing data from Joule’s in-memory database.
- [Transformation](https://docs.fractalworks.io/joule/components/processors/transformation.md): Reshape origin event data in to target event
- [Field Tokeniser](https://docs.fractalworks.io/joule/components/processors/transformation/field-tokeniser.md): Tokenise attribute values in to component parts
- [Obfuscation](https://docs.fractalworks.io/joule/components/processors/transformation/obfuscation.md): Joule provides an in-stream-obfruscation function to streaming events. This function is useful for Personal Identifiable Information de-identification.
- [Encryption](https://docs.fractalworks.io/joule/components/processors/transformation/obfuscation/encryption.md): Apply RSA encryption techniques along with AES symmetric encryption
- [Masking](https://docs.fractalworks.io/joule/components/processors/transformation/obfuscation/masking.md): Mask sensitive field values while retaining the formatting criteria
- [Bucketing](https://docs.fractalworks.io/joule/components/processors/transformation/obfuscation/bucketing.md): Apply individual variance tolerances to protect the identity of the originating data
- [Redaction](https://docs.fractalworks.io/joule/components/processors/transformation/obfuscation/redaction.md): Eliminate sensitive event field data by either nullifying or replacing with a blank value
- [Triggers](https://docs.fractalworks.io/joule/components/processors/triggers.md): Minimise expensive computation while notifying consumers of events to action
- [Change Data Capture](https://docs.fractalworks.io/joule/components/processors/triggers/change-data-capture.md): Distribute delta records for key attribute changes
- [Business rules](https://docs.fractalworks.io/joule/components/processors/triggers/business-rules.md): Leverage standard JSR-94 rules engine to perform advance business rules
- [Stream join](https://docs.fractalworks.io/joule/components/processors/stream-join.md): Join independent stream events to trigger advanced analytics and dynamic business rules
- [Inner stream joins](https://docs.fractalworks.io/joule/components/processors/stream-join/inner-stream-joins.md): Strict join between two event streams
- [Outer stream joins](https://docs.fractalworks.io/joule/components/processors/stream-join/outer-stream-joins.md): Immediately pass the first event received and initialised downstream processors
- [Join attributes & policy](https://docs.fractalworks.io/joule/components/processors/stream-join/join-attributes-and-policy.md): Join attributes to control and optimise performance
- [Event tap](https://docs.fractalworks.io/joule/components/processors/event-tap.md): Tap events directly in to an in-memory database to enable on / offline processing
- [Anatomy of a Tap](https://docs.fractalworks.io/joule/components/processors/event-tap/anatomy-of-a-tap.md): Construction of a Tap
- [SQL Queries](https://docs.fractalworks.io/joule/components/processors/event-tap/sql-queries.md): Use SQL queries to access the data in the store
- [Analytics](https://docs.fractalworks.io/joule/components/analytics.md): Analytics sit at the heart of the Joule platform, transforming raw data into actionable insights that drive real-world value
- [Analytic tools](https://docs.fractalworks.io/joule/components/analytics/analytic-tools.md): Define math expressions or provide as a file using Joule supported languages and APIs
- [User defined analytics](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/user-defined-analytics.md): Define analytic expressions or provide as a script using supported interpreted languages
- [Streaming analytics example](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/user-defined-analytics/streaming-analytics-example.md): Example on how to run streaming analytics
- [User defined analytics](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/user-defined-analytics/user-defined-analytics.md): Declarative stateful math expressions evaluated in real-time
- [User defined scripts](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/user-defined-analytics/user-defined-scripts.md): Leverage pre-existing analytics scripts within a streaming context
- [User defined functions](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/user-defined-analytics/user-defined-functions.md): Extend the analytics ecosystem using the Analytics API
- [Average function library](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/user-defined-analytics/user-defined-functions/average-function-library.md): Joule math functions
- [Window analytics](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/window-analytics.md): Standard window functions are provided to perform event based analytics
- [Tumbling window](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/window-analytics/tumbling-window.md): Fixed-sized, non-overlapping window analytic function support
- [Sliding window](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/window-analytics/sliding-window.md): Fixed-sized, overlapping time or event count window analytic function support
- [Aggregate functions](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/window-analytics/aggregate-functions.md): Standard statistics calculations for streaming event windows
- [Analytic functions](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/analytic-functions.md): Analytic functions perform complex calculation over a window of grouped events
- [Stateful](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/analytic-functions/stateful.md): Stateful based analytics over a grouped set of events
- [Exponential moving average](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/analytic-functions/stateful/exponential-moving-average.md)
- [Rolling Sum](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/analytic-functions/stateful/rolling-sum.md)
- [Stateless](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/analytic-functions/stateless.md): Stateless based analytics over a grouped set of events
- [Normalisation](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/analytic-functions/stateless/normalisation.md): Change the distribution shape of your data
- [Absolute max](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/analytic-functions/stateless/normalisation/absolute-max.md)
- [Min max](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/analytic-functions/stateless/normalisation/min-max.md)
- [Standardisation](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/analytic-functions/stateless/normalisation/standardisation.md)
- [Mean](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/analytic-functions/stateless/normalisation/mean.md)
- [Log](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/analytic-functions/stateless/normalisation/log.md)
- [Z-Score](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/analytic-functions/stateless/normalisation/z-score.md)
- [Scaling](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/analytic-functions/stateless/scaling.md): Change the range of your data
- [Unit scale](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/analytic-functions/stateless/scaling/unit-scale.md)
- [Robust Scale](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/analytic-functions/stateless/scaling/robust-scale.md)
- [Statistics](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/analytic-functions/stateless/statistics.md): Key statistical functions and measures
- [Statistic summaries](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/analytic-functions/stateless/statistics/statistic-summaries.md)
- [Weighted moving average](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/analytic-functions/stateless/statistics/weighted-moving-average.md)
- [Simple moving average](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/analytic-functions/stateless/statistics/simple-moving-average.md)
- [Count](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/analytic-functions/stateless/statistics/count.md)
- [General](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/analytic-functions/stateless/general.md): Utility and supporting analytic functions
- [Euclidean](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/analytic-functions/stateless/general/euclidean.md)
- [Advanced analytics](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/advanced-analytics.md): Advanced analytic processors such as geospatial tracking
- [Geospatial](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/advanced-analytics/geospatial.md): Optimised real-time geospatial analytics for geofence occupancy and tracking
- [Entity geo tracker](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/advanced-analytics/geospatial/entity-geo-tracker.md): Real-time entity geo tracking for advanced use cases
- [Geofence occupancy trigger](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/advanced-analytics/geospatial/geofence-occupancy-trigger.md): Trigger geospatial events in real-time to drive location based use cases
- [Geo search](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/advanced-analytics/geospatial/geo-search.md): Real-time view on what entities are nearby with respect to geofence radius
- [IP address resolver](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/advanced-analytics/geospatial/ip-address-resolver.md): Take an IP address and perform a geo location search
- [Reverse geocoding](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/advanced-analytics/geospatial/reverse-geocoding.md): Google reverse geocode using longitude and latitude to street address
- [Spatial Index](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/advanced-analytics/geospatial/spatial-index.md): Optimised data structure for spatial search
- [HyperLogLog](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/advanced-analytics/hyperloglog.md): Probabilistic counter for large or high cardinality datasets
- [Distinct counter](https://docs.fractalworks.io/joule/components/analytics/analytic-tools/advanced-analytics/distinct-counter.md): Calculate distinct field values over time
- [ML inferencing](https://docs.fractalworks.io/joule/components/analytics/ml-inferencing.md): Leverage streaming online predictions to drive insights to action
- [Key concepts](https://docs.fractalworks.io/joule/components/analytics/ml-inferencing/key-concepts.md)
- [Feature engineering](https://docs.fractalworks.io/joule/components/analytics/ml-inferencing/feature-engineering.md): Decorate a feature vector with enriched features specific to the deployed model
- [Scripting](https://docs.fractalworks.io/joule/components/analytics/ml-inferencing/feature-engineering/scripting.md): Define custom analytics with declarative expressions
- [Scaling](https://docs.fractalworks.io/joule/components/analytics/ml-inferencing/feature-engineering/scaling.md): Normalise data with various scaling methods
- [Transform](https://docs.fractalworks.io/joule/components/analytics/ml-inferencing/feature-engineering/transform.md): Generate analytics-ready features from data
- [Online predictive analytics](https://docs.fractalworks.io/joule/components/analytics/ml-inferencing/online-predictive-analytics.md): JPMML prediction processor evaluates event feature vectors in near-real-time
- [Model audit](https://docs.fractalworks.io/joule/components/analytics/ml-inferencing/model-audit.md): Support explainability, detect drift, and manage retraining through model auditing
- [Model management](https://docs.fractalworks.io/joule/components/analytics/ml-inferencing/model-management.md): Deploy a retrained model directly in to a running Joule with zero down time
- [Metrics engine](https://docs.fractalworks.io/joule/components/analytics/metrics-engine.md): In-memory SQL compliant metrics engine for advance analytics solutions
- [Create metrics](https://docs.fractalworks.io/joule/components/analytics/metrics-engine/create-metrics.md): Define a set of time based metrics that are generated using captured and stored streamed events
- [Apply metrics](https://docs.fractalworks.io/joule/components/analytics/metrics-engine/apply-metrics.md): Apply metrics within stream processing functions
- [Manage metrics](https://docs.fractalworks.io/joule/components/analytics/metrics-engine/manage-metrics.md): Reuse existing metrics on startup and reduce the operational memory overhead
- [Priming metrics](https://docs.fractalworks.io/joule/components/analytics/metrics-engine/priming-metrics.md): Prime metrics with existing values on process startup
- [Exporting metrics](https://docs.fractalworks.io/joule/components/analytics/metrics-engine/exporting-metrics.md)
- [Contextual data](https://docs.fractalworks.io/joule/components/contextual-data.md): Enrich real-time streams with contextual data
- [Architecture](https://docs.fractalworks.io/joule/components/contextual-data/architecture.md): Understand how Joule integrates to contextual data solutions
- [Configuration](https://docs.fractalworks.io/joule/components/contextual-data/configuration.md): Set up a contextual data-driven use case
- [MinIO S3](https://docs.fractalworks.io/joule/components/contextual-data/minio-s3.md): Multi-cloud S3-compatible interface for static contextual data and ML models
- [Apache Geode](https://docs.fractalworks.io/joule/components/contextual-data/apache-geode.md): High-performance caching platform for static and slow-moving contextual data
- [Connectors](https://docs.fractalworks.io/joule/components/connectors.md): Out-of-the-box Joule provides key data connectors for streaming use cases
- [Sources](https://docs.fractalworks.io/joule/components/connectors/sources.md): Connect to key event and file data sources
- [Kafka](https://docs.fractalworks.io/joule/components/connectors/sources/kafka.md): Standard Kafka consumers transport ingests data from subscribed cluster topics
- [Ingestion](https://docs.fractalworks.io/joule/components/connectors/sources/kafka/ingestion.md): Joule enables flexible Kafka data deserialisation for processing
- [RabbitMQ](https://docs.fractalworks.io/joule/components/connectors/sources/rabbitmq.md): AMQP messaging solution ideal for IoT and client / server use cases
- [Further RabbitMQ configurations](https://docs.fractalworks.io/joule/components/connectors/sources/rabbitmq/further-rabbitmq-configurations.md): Further collection of examples using RabbitMQ
- [MQTT](https://docs.fractalworks.io/joule/components/connectors/sources/mqtt.md): Lightweight messaging protocol ideal for IoT use cases
- [Topic wildcards](https://docs.fractalworks.io/joule/components/connectors/sources/mqtt/topic-wildcards.md)
- [Session management](https://docs.fractalworks.io/joule/components/connectors/sources/mqtt/session-management.md)
- [Last Will and Testament](https://docs.fractalworks.io/joule/components/connectors/sources/mqtt/last-will-and-testament.md)
- [Rest endpoints](https://docs.fractalworks.io/joule/components/connectors/sources/rest-endpoints.md): RESTful consumer endpoints designed to facilitate seamless integration
- [MinIO S3](https://docs.fractalworks.io/joule/components/connectors/sources/minio-s3.md): MinIO S3 file consumer for cloud or local hosted bucket storage
- [Google sheets](https://docs.fractalworks.io/joule/components/connectors/sources/google-sheets.md): Spreadsheet data consumer designed to extend processing capabilites
- [File watcher](https://docs.fractalworks.io/joule/components/connectors/sources/file-watcher.md): Process large files using stream processing
- [Sinks](https://docs.fractalworks.io/joule/components/connectors/sinks.md): Distribute insights to consuming systems
- [Kafka](https://docs.fractalworks.io/joule/components/connectors/sinks/kafka.md): Sends events to specified Kafka topics, enabling real-time data streams
- [RabbitMQ](https://docs.fractalworks.io/joule/components/connectors/sinks/rabbitmq.md): RabbitMQ is lightweight and easy to deploy messaging platform for event-based data integration
- [Further configurations](https://docs.fractalworks.io/joule/components/connectors/sinks/rabbitmq/further-configurations.md): Further RabbitMQ distribution configurations
- [MQTT](https://docs.fractalworks.io/joule/components/connectors/sinks/mqtt.md): Allows publishing events through MQTT, ideal for IoT and lightweight streaming
- [Persistent messaging](https://docs.fractalworks.io/joule/components/connectors/sinks/mqtt/persistent-messaging.md)
- [Last Will and Testament](https://docs.fractalworks.io/joule/components/connectors/sinks/mqtt/last-will-and-testament.md)
- [SQL databases](https://docs.fractalworks.io/joule/components/connectors/sinks/sql-databases.md): Write events in micro batches to any database which supports JDBC Type 4 drivers
- [InfluxDB](https://docs.fractalworks.io/joule/components/connectors/sinks/influxdb.md): Standard time-series database idea for instrumentation or live KPI tracking
- [MongoDB](https://docs.fractalworks.io/joule/components/connectors/sinks/mongodb.md): Publish JSON based events to the mature standard document storePublishes JSON-based events to MongoDB, a widely-used document store
- [Geode](https://docs.fractalworks.io/joule/components/connectors/sinks/geode.md): Integrate with distributed caching for complex use cases needing high availability
- [WebSocket](https://docs.fractalworks.io/joule/components/connectors/sinks/websocket.md): Publishes processed events to web clients via WebSocket transport, ideal for real-time dashboards and applications
- [Google sheets](https://docs.fractalworks.io/joule/components/connectors/sinks/google-sheets.md): Spreadsheet data publisher designed to extend processing capabilites
- [Console](https://docs.fractalworks.io/joule/components/connectors/sinks/console.md): For testing purposes a console output processor is provided.
- [MinIO S3](https://docs.fractalworks.io/joule/components/connectors/sinks/minio-s3.md): MinIO file producer using S3 cloud or local hosted buckets
- [Custom connectors](https://docs.fractalworks.io/joule/components/connectors/sinks/custom-connectors.md)
- [File](https://docs.fractalworks.io/joule/components/connectors/sinks/custom-connectors/file.md): Write events directly to files for archiving and offline processing
- [Slack](https://docs.fractalworks.io/joule/components/connectors/sinks/custom-connectors/slack.md): Send critical alerts to a monitored Slack channel
- [Email](https://docs.fractalworks.io/joule/components/connectors/sinks/custom-connectors/email.md): Send critical email alerts to key stakeholders
- [Serialisers](https://docs.fractalworks.io/joule/components/connectors/serialisers.md): Get data ready for consumption serialising incoming and outgoing data
- [Serialisation](https://docs.fractalworks.io/joule/components/connectors/serialisers/serialisation.md): Data emitted to downstream systems is serialised using provided or custom serialisers
- [Custom transform example](https://docs.fractalworks.io/joule/components/connectors/serialisers/serialisation/custom-transform-example.md): Custom parser converts an internal Joule StreamEvent into a domain object
- [Formatters](https://docs.fractalworks.io/joule/components/connectors/serialisers/serialisation/formatters.md): Apply standard data format process to outgoing data
- [Deserialisers](https://docs.fractalworks.io/joule/components/connectors/serialisers/deserialisers.md): Consumed data is mapped to internal StreamEvents using a flexible deserialisation framework
- [Custom parsing example](https://docs.fractalworks.io/joule/components/connectors/serialisers/deserialisers/custom-parsing-example.md): Custom parser converts a domain Quote object into an internal Joule StreamEvent
- [Observability](https://docs.fractalworks.io/joule/components/observability.md): Joule uses JMX and Metrics API to make processes observable and to enable monitoring
- [Enabling JMX for Joule](https://docs.fractalworks.io/joule/components/observability/enabling-jmx-for-joule.md): Activate JMX monitoring for Joule with configurable settings
- [Meters](https://docs.fractalworks.io/joule/components/observability/meters.md): Automated metrics monitor for Joule pipelines: data pipelines, processors, transport, storage
- [Metrics API](https://docs.fractalworks.io/joule/components/observability/metrics-api.md): Tracks component events and data flow with counters