Cassandra
Apache Cassandra is a distributed NoSQL database that handles massive amounts of scraped data with high availability and linear scalability.
Cassandra is a powerful, distributed NoSQL database designed for high availability and massive scalability.
Key Features:
- Linear Scalability - Add nodes to increase capacity and throughput with operational planning for replication and load.
- High Availability - Peer-to-peer architecture with no single point of failure supports availability subject to replica health and consistency settings.
- Multi-Data Center - Replicate data across regions for disaster recovery and low-latency global access.
- Tunable Consistency - Balance consistency and availability per query to match your requirements.
- Wide-Column Model - Store scraped data with flexible schemas that evolve without migrations.
Whether you're storing billions of scraped records, building globally distributed data stores, or running high-write workloads, Cassandra provides the resilience and scale your infrastructure demands.
Web scraping workflow
How to use Cassandra in a web scraping pipeline
Apache Cassandra stores partitioned rows identified by primary keys. In a scraping system, it can hold repeated observations when retrieval patterns are known in advance, such as reading a source's records for a specific collection period.
A practical workflow
- A separate crawler extracts records with a source identifier, entity key and observation time.
- Your loader maps those fields to a deliberately chosen partition and clustering-key design, then writes normalized rows to Cassandra.
- A consumer reads the intended key ranges and builds an export or serves the collected observations to an application.
When it fits
Consider it when the application already needs a distributed row store and has predictable queries. Model the table around those queries before connecting the scraper, rather than copying arbitrary page fields into a generic table.
Boundaries
Cassandra does not fetch pages or decide which observations are duplicates. Partition sizing, consistency settings and retention need explicit design. Keep large raw captures elsewhere and preserve their references; database distribution alone does not validate extraction or provide unrestricted relational analytics.
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apache/cassandra
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10.1KForks
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2026-10-15License
Apache-2.0Language
Java
Metrics recorded 2026-10-16
Repository details
License source: Repository license file
Frequently asked questions
What is the main purpose of Cassandra?
Apache Cassandra is a distributed NoSQL database for storing large datasets across multiple nodes. Replication and partitioning let applications spread data and traffic across the cluster.
Sources (checked ): Cassandra architecture overview
Is Cassandra a SQL or NoSQL database?
Cassandra is a distributed NoSQL database with a partitioned wide-column storage model. Its Cassandra Query Language (CQL) has SQL-like syntax, but the database’s capabilities differ from a relational system: it does not provide distributed joins or foreign keys.
Sources (checked ): Cassandra storage model and CQL
Is Cassandra better than MongoDB?
Their data models suit different requirements. Cassandra uses partitioned wide-column tables and is designed around distributed, partition-oriented queries. MongoDB stores documents and supports embedded or referenced relationships. Compare your access patterns, schema and operational requirements rather than treating either database as universally better.
Sources (checked ): Cassandra architecture; MongoDB data modeling
What is the difference between Cassandra and DynamoDB?
Cassandra is an open-source distributed database whose cluster you can operate yourself. Amazon DynamoDB is an AWS-managed NoSQL service supporting key-value and document data. Compare their data models, query requirements and operational responsibilities when deciding which fits an application.
Sources (checked ): Cassandra overview; Amazon DynamoDB introduction
Sources
Verified against the apache/cassandra repository and the PyPI package.