01 Introduction

Document databases deviate from the entity-based denormalized data model of relational dbs and prefer an approach based on denormalized and aggregated data typical of business document.

A document is a complex object made up of what would be many different SQL tables, and so it can be composed of different pieces of data with different struc- tures.

Some of the advantages of document stores are:

• Flexible structure that handles well schema changes
• Solves mismatches impedance problems: document structure is more in line with how developers construct classes
• JSON compatibility, which guarantees very ease of integration with web technologies

Sharding

Sharding is a means of partitioning data across servers to enable:

• Scale: needed by Modern applications to support massive workloads and data volume.
• Geo-Locality: to support geographically distributed deployments to support optimal UX for customers across vast geographies.
• Hardware Optimizations: on Performance vs. Cost
• Lower Recovery Times: to make “Recovery Time Objectives” (RTO) feasible.

Sharding involves a shard key defined by a data modeler that describes the partition space of a data set.

Data is partitioned into data chunks by the shard key, and these chunks are distributed evenly across shards that reside across many physical servers