Tenzir
Tenzir is a data pipeline engine specifically designed for security teams, facilitating the collection, transformation, enrichment, and routing of security data throughout its lifecycle. It enables users to seamlessly gather data from various sources, parse unstructured data into structured formats, and transform it as needed. It optimizes data volume, reduces costs, and supports mapping to standardized schemas like OCSF, ASIM, and ECS. Tenzir ensures compliance through data anonymization features and enriches data by adding context from threats, assets, and vulnerabilities. It supports real-time detection and stores data efficiently in Parquet format within object storage systems. Users can rapidly search and materialize necessary data and reactivate at-rest data back into motion. Tension is built for flexibility, allowing deployment as code and integration into existing workflows, ultimately aiming to reduce SIEM costs and provide full control.
Learn more
Dropbase
Centralize offline data, import files, process and clean up data. Export to a live database with 1 click. Streamline data workflows. Centralize offline data and make it accessible to your team. Bring offline files to Dropbase. Multiple formats. Any way you like. Process and format data. Add, edit, re-order, and delete processing steps. 1-click exports. Export to database, endpoints, or download code with 1 click. Instant REST API access. Query Dropbase data securely with REST API access keys. Onboard data where you need it. Combine and process datasets to fit the desired format or data model. No code. Process your data pipelines using a spreadsheet interface. Track every step. Flexible. Use a library of pre-built processing functions. Or write your own. 1-click exports. Export to database or generate endpoints with 1 click. Manage databases. Manage and databases and credentials.
Learn more
Upsolver
Upsolver makes it incredibly simple to build a governed data lake and to manage, integrate and prepare streaming data for analysis. Define pipelines using only SQL on auto-generated schema-on-read. Easy visual IDE to accelerate building pipelines. Add Upserts and Deletes to data lake tables. Blend streaming and large-scale batch data. Automated schema evolution and reprocessing from previous state. Automatic orchestration of pipelines (no DAGs). Fully-managed execution at scale. Strong consistency guarantee over object storage. Near-zero maintenance overhead for analytics-ready data. Built-in hygiene for data lake tables including columnar formats, partitioning, compaction and vacuuming. 100,000 events per second (billions daily) at low cost. Continuous lock-free compaction to avoid “small files” problem. Parquet-based tables for fast queries.
Learn more
APITube
APITube is a News API that turns global news coverage into structured JSON. It aggregates articles from 500,000+ verified sources across 180+ countries in 60+ languages, and enriches every article before delivery: sentiment scores, extracted entities (people, organizations, locations, brands), IPTC categories, topics and industries.
Developers query one search endpoint with 65+ filter parameters — keywords, language, country, source domain, source quality rank, sentiment range, entity IDs, media presence, date ranges — combined in a single request. Separate endpoints cover top headlines, clustered stories, trending values over time buckets, and a live Server-Sent Events stream; webhooks push new matches as they are indexed.
Responses are JSON by default, with XML, CSV, TSV, XLSX, JSONL and Parquet exports on paid plans. Authentication is a single API key, and a hosted MCP server exposes the same search to AI assistants.
Learn more
