Apache Druid Pricing & Plans

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Segment Partitioning

Data is divided into time-based immutable segments for efficient pruning and query targeting.

Columnar Encoding

Stores data in column-oriented layout, enabling selective access and reduced I/O per query.

Bitmap Indexing

Builds compressed bitmap indexes on dimensions for fast multi-value filtering and lookup.

Dictionary Encoding

Encodes dimension values into integer IDs to reduce storage footprint and accelerate scans.

Realtime Ingestion

Streams from Kafka/Kinesis are ingested continuously, making data queryable on arrival.

Batch Ingestion

Ingests files from Hadoop, S3, or local sources in batch jobs to build optimized segments.

Roll-Up Aggregation

Aggregates rows during ingestion to reduce row counts and improve query performance.

Segment Versioning

Manages segment updates by versioning; new versions atomically replace old ones.

Segment Replication

Replicates segments across nodes for fault tolerance and high query availability

Query Caching

Caches intermediate query results at broker and historical nodes for faster re-execution.

Time Chunk Pruning

Skips irrelevant segments during queries by leveraging time-based partitioning.

Segment Compaction

Periodically merges small segments into larger ones to optimize storage and scans.

Task Scheduling

MiddleManager and Indexer nodes coordinate ingestion tasks in parallel for scaling.

Data Retention Management

Automatically drops or archives old segments based on retention rules.

Load Balancing

Balances query load across historical and real-time nodes to maintain performance.

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Brand Name	The Apache Software Foundation
Information	Apache Software Foundation provides organizational, legal and financial support for Apache open-source software projects.
Founded Year	1999
Director/Founders	Brian Behlendorf, Grant Ingersoll, Isabel Drost-Fromm, Jim Jagielski, Lars Eilebrecht, Patrick Stued
Company Size	1-100 Employees
Other Products	Apache SkyWalking, Glowroot, Apache Storm, Apache Drill, Apache Airflow