For analytical use cases, you can gain significant performance and cost advantages by syncing the DynamoDB table with a different tool or service like Rockset.
Many development teams turn to DynamoDB for building event-driven architectures and user-friendly, performant applications at scale. As an operational database, DynamoDB is optimized for real-time transactions even when deployed across multiple geographic locations. However, it does not provide strong performance for search and analytics access patterns.
This means resources are often overprovisioned because they cannot be independently scaled. In addition, multiple workloads, such as reads and writes, will contend for the same compute resources. Elasticsearch also cannot handle updates efficiently. Updating any field will trigger a reindexing of the entire document. Elasticsearch documents are immutable, so any update requires a new document to be indexed and the old version marked deleted.
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