The tremendous growth in volumes of data — both traditional structured data and new data types, such as Internet-of-Things (IoT) — and the advent of in-memory
database technologies like SAP’s HANA and NAND flash storage, which are faster but more expensive, has made data archiving mandatory. Companies simply cannot afford to operate as they once did, allowing years of data, much of it seldom used, to accumulate in single tier databases. The old data clogs systems, hurting performance, and, when that database is running on flash or in-memory, it also becomes prohibitively expensive.
For too long, organizations have debated the best way to manage the lifecycle of application data. Organizations want to implement true ILM to ensure governance, data security, and operational efficiency.
While unstructured data archiving is relatively simple as it is primarily based on age, structured data archiving is complex requiring that multiple criteria be factored into the process.
The best way to improve the management of enterprise data is to create tiers of data based on value. Our recommended ILM best practice is to leverage four processing tiers integrated with Apache Hadoop.
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