# Overview *2-3 sentences on the description of the product* ## Architecture Diagram ## Summary Characteristics | Type | License | Data Models | ACID | Consistency | Price | Website | | ---- | ------- | ----------- | ---- | ----------- | ----- | ------- | | | | | | | | | ## Pro and Cons Summary ### Pros ### Cons ### Limitations # Use Cases # Key Features ## Lucene Indexes ### Lucene Segments Lucene segments are immutable containers for indexed data. The process for writing the segments is a batch process. As inserts, deletes, and updates are requested they are batched up for execution: - Inserts - documents are added to a segment as they are inserted. Once a batch is ready, they are written to disk. - When segments get too big, they can be merged and the previous segments can be removed. - Deletes - the segments use deletion identifiers to hide documents during search. They are node deleted until a merge operation. - Updates - a soft delete is used on the old document and a new document is inserted. They are not fully deleted until a merge operation. #### Inverted Index and Doc Values Lucene uses an [[Inverted Index]] to optimize search. Doc values are fields stored in a columnar, contiguous representation across all documents to allow for efficient sorting. # Key Characteristics ## Data Storage and Indexing Mechanisms ### [[Locality]] ## High Availability and Fault Tolerance Mechanisms ### Replication and Sharding Options ### Concurrency and Consistency Models # Performance ## Known Scalability Limits ## Tuning and Optimization Tips # Ecosystem and Integration ## Compatibility with other Tools ## Available Drivers and SDKs # Security ## Authentication Methods ## Encryption # Notable Users # Documentation Links # Alternatives | Product | Why Consider | | ------- | ------------ | | | | ## Reference #### Working Notes #### Sources