Tika

Content analysis toolkit that detects and extracts metadata and structured text from over a thousand file types. Provides a single unified interface to parse PDFs, Office documents, images, archives, and many other formats without handling each format separately. Useful for search indexing, content analysis, translation pipelines, and document processing workflows.

Apache Tika is an Apache Software Foundation project, formerly a subproject of Apache Lucene. It underpins document analysis in Apache Solr and was a key technology in the Panama Papers investigation. Compared to format-specific libraries, Tika offers one API for hundreds of parsers and detectors, with MIME detection, metadata extraction, and OCR support via optional Tesseract integration.

Key features:

• 1000+ file types supported through a single Parser and Detector interface
• REST server for language-agnostic integration via HTTP
• MIME type detection and metadata extraction from documents
• Java library for embedding in applications and batch processing via tika-pipes
• Optional OCR via Tesseract and language detection

Search engine indexing pipelines feed documents through Tika before indexing in Solr or Elasticsearch. Content management systems use it to extract text and metadata for full-text search and faceted browsing. ETL and data pipelines rely on Tika for normalizing heterogeneous document stores. Developers embed the Java library or call tika-server via HTTP for document processing in any language.