Curated for content, computing, and digital experience professionals

Day: March 8, 2023

Ontotext releases GraphDB 10.2

Ontotext, a provider of enterprise knowledge graph (EKG) technology and semantic database engines, launched GraphDB 10.2, an RDF database for knowledge graph. GraphDB enables organizations to link diverse data, index it for semantic search, and enrich it via text analysis to build large scale knowledge graphs. With improved cluster backup and cloud support, GraphDB lowers traditional memory requirements, and provides a more transparent memory model.

Users can oversee system health and diagnose problems easier using industry-standard toolkit Prometheus or by monitoring performance directly within the GraphDB Workbench itself. The solution also includes support for X.509 client certificate authentication for greater flexibility when accessing a secured GraphDB instance.

Backups can also be stored directly in Amazon S3 storage to ensure the most up to date data is securely protected against inadvertent changes or hardware failures in local on-prem infrastructure.

Internal structures and moved memory usage from off-heap to the Java heap were also redesigned for a more straightforward memory configuration, where a single number i.e. (the Java maximum heap size) controls the maximum memory available to GraphDB. Memory used during RDF Rank computation was also optimized making it possible to compute the rank of larger repositories with less memory.

Gilbane Advisor 3-8-23 — LLMs, KBs & LlamaIndex, BigQuery + Search Console

This week we feature articles by Purvanshi Mehta, and Daniel Waisberg, Gaal Yahas, & Haim Daniel.

Additional reading from Jeremy Perdue, Rachel Gordon, and Nandan Grover.

News comes from Quark, TigerGraph, Slang Labs, and DeltaXML.

Note that news items now link to the original source of the news rather than our 200 word summaries, which are always available here.

All previous issues are available at

Opinion / Analysis

Indexing and Querying external KBs through GPT — GPT Index (LlamaIndex)

Purvanshi Mehta provides an overview of how you can use the GPT Index (now LlamaIndex) to customize large language models by connecting with external knowledge bases relevant to your application domain. She helpfully includes examples for different types of data sources. (6 min).

Bulk data export: a new and powerful way to access your Search Console data

From the Google Search Console Team…

You can configure an export in Search Console to get a daily data dump into your BigQuery project. The data includes all your performance data, apart from anonymized queries, which are filtered out for privacy reasons … This means you can explore your data to its maximum potential, joining it with other sources of data and using advanced analysis and visualization techniques. … This data export could be particularly helpful for large websites with tens of thousands of pages, or those receiving traffic from tens of thousands of queries a day (or both!). (3 min).

More Reading

All Gilbane Advisor issues

Content technology news

Quark releases Quark Publishing Platform NextGen v3.0

The content automation platform is designed to simplify the complexities associated with enterprise content lifecycle management. ■

TigerGraph expands cloud capabilities

Provides a comprehensive, streamlined approach to deploy and maintain multiple graph database solutions with visual analytics and machine learning tools.

Slang Labs launches CONVA

CONVA is a full-stack solution that provides smart and highly accurate multilingual voice search capabilities inside e-commerce apps.

DeltaXML eases HTML table comparison with XML Compare 14

The finer-grained detail for cells and rows are easier to display and provide greater understanding when reviewed.

All content technology news

The Gilbane Advisor is authored by Frank Gilbane and is ad-free, cost-free, and curated for content, computing, web, data, and digital experience technology and information professionals. We publish recommended articles and content technology news weekly. We do not sell or share personal data.

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