HPE Ezmeral Data Fabric Database supports JSON documents as a native data store. A JSON document is a tree of
fields. These JSON documents are stored in HPE Ezmeral Data Fabric Database tables.
HPE Ezmeral Data Fabric Database as a document database, implements JSON documents in HPE Ezmeral Data Fabric Database JSON tables.
- HPE Ezmeral Data Fabric Database JSON tables use the OJAI data model and support the OJAI API.
- Documents are in JSON format; HPE Ezmeral Data Fabric Database stores them in an efficient binary encoding,
rather than plain ASCII text.
- With JSON tables, each value has a unique key (
_id). You identify
fields in the document using field paths. For example, address.street:
{
"_id": "ID001",
"name" : "Bob",
"address": {
"house" : 123,
"street": "Main",
"phones": [
{ "mobile": "555-1234" },
{ "work": "+1-123-456-7890" }]},
"hobbies": ["badminton", "chess", "beaches"]
} Note: Each
JSON document can have different fields.
With JSON document support, you can:
- Store data that is hierarchical and nested, and evolves over time.
- Read and write individual document fields, subsets of fields, or whole
documents from and to disk. To update individual fields or subsets of fields, there is no
need to read entire documents, modify them, and then write the modified documents to disk.
- Build applications with the HPE Ezmeral Data Fabric Database JSON API library, which is an
implementation of the Open
JSON Application Interface (OJAI). This is an API library for easily managing
complex, evolving, hierarchical data. You can use more data types than the standard types
that JSON supports, create complex queries, and access JSON table documents without
connection or configuration objects. This allows large-scale applications to manage JSON
documents.
- Filter query results within HPE Ezmeral Data Fabric Database before results are returned to client
applications.
- Run client applications on Linux, OS X, and Windows systems.
- Perform complex data analysis on your JSON data with Apache Drill or other
analytical tools in real time without having to copy data to another cluster.
- Scale your data to span thousands of nodes.
- Control read and write access to single fields and subsets of fields within a
JSON table by using
access-control expressions (ACEs).
- Control the disk layout of single fields and subdocuments within JSON
tables.
- Use Secondary Indexes to improve query
performance.