If your enterprise is shopping for a new database or data platform, there’s a lot of key questions to answer.
To help you make the right choice, database vendors will tout the power of their tools for data analysis, storage, querying, visualization, and more. And these are all key considerations. But there’s another important factor few vendors talk about: data import.
Data import matters – a lot.
Your backend data platform is only as useful as the data that’s actually in it. If it’s difficult to import your data – let alone update existing data or ingest new data sources – then you lose any other advantages that a given platform offers. There’s no getting around it: you need a database platform that ingests your data quickly and effectively.
Here’s how GraphGrid Ingest – part of the GraphGrid – makes your data import process both easy and effective.
Using GraphGrid Ingest for Data Import
GraphGrid Ingest imports your data into a graph database that can be accessed and analyzed using other GraphGrid services. During import, GraphGrid Ingest transforms your disparate data into a knowledge graph of connected data.
Ingest lets you define how values in your source database map to a property graph data model, representing nodes, relationships, and properties in GraphGrid. Or, if you don’t have the time or expertise to create a detailed policy map, the Ingest service can also convert these values using standard formats.
For initial data loading, GraphGrid Ingest supports all of the following formats and methods:
- LOAD CSV
Automating Data Import into Your Knowledge Graph
Having a smooth data import experience with a new database or data platform is critical, but data import isn’t a one-and-done process.
Today’s enterprise organizations – and their respective AI solutions – depend on up-to-the-minute intel in order to make mission-critical choices. Waiting to load or process new data in batches means your team’s data-driven decisions might lack the most recent information or critical context.
In the end, you risk making the wrong decision despite having the data readily available – but not yet imported into your knowledge graph. GraphGrid Ingest helps ensure that doesn’t happen.
In addition to the initial data import, GraphGrid Ingest also continuously updates your graph database with new information as it’s made available. For example, you can configure GraphGrid Ingest to subscribe to designated RSS feeds, and Ingest will then automatically consume the articles found in the feed and process them using NLP, turning them into a graph format and loading them into Connected Data Platform. These new nodes, relationships, and properties are added to your current graph data – or updated where they already exist.
What’s more, this data ingestion process is fast with parallelized writes to the graph. Because when the success of a venture or mission is on the line, speed matters.
These RSS ingestion capabilities can also be used alongside GraphGrid’s Natural Language Processing (NLP) service.
By using RSS Ingest and NLP together, your development team has the power to automate the process of adding and annotating text nodes in your graph database. In turn, you can gain further insight into your newly collected and processed data by using GraphGrid NLP’s similarity clustering capability.
For teams or organizations that don’t require up-to-the-minute data, GraphGrid Ingest also includes batching options for data import. So there’s no need to build and manage a complex write pipeline if you don’t need one.
Real-time access to information – both new and existing – is critical for making well-informed decisions. If your enterprise is currently comparing potential data platforms, don’t overlook the value of data import capabilities.
Your backend infrastructure needs to seamlessly integrate new data that’s accessible in real-time. GraphGrid Connected Data Platform makes it happen.
See for yourself:
Take GraphGrid for a test drive.