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AWS Glue Malta

AWS Glue implementation for Malta businesses on AWS. Neural AI builds serverless ETL pipelines, data catalogues.

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/ the solution /

AWS Glue built around your business.

Every solution we deliver is built on three pillars: your data, your context, and continuous improvement. Each capability is traceable and measurable.

  • Serverless ETL Pipeline Development

    Neural AI builds AWS Glue ETL jobs for Malta businesses — serverless Spark-based data processing that scales automatically without cluster management. Glue jobs process data from S3, RDS, Redshift, DynamoDB, and other AWS sources, applying transformations using Python (PySpark) or Scala. We implement Glue jobs for Malta data engineering requirements — data cleaning, format conversion, schema normalisation, and loading analytical targets — with Glue's automatic worker scaling eliminating capacity planning.

  • AWS Glue Data Catalog

    We implement the AWS Glue Data Catalog as the metadata repository for Malta business data lake assets — crawling S3 data lake directories, RDS databases, and Redshift to automatically discover and register tables, schemas, and partitions. The Glue Data Catalog integrates with Athena, Redshift Spectrum, and EMR, providing a unified metadata layer that enables SQL querying across Malta data lake assets without data movement.

  • AWS Glue DataBrew

    We use AWS Glue DataBrew for visual data preparation — providing a no-code interface for cleaning, normalising, and transforming Malta business data. DataBrew's 250+ pre-built transformations handle common data quality issues without Spark code: date parsing, string manipulation, outlier handling, and format standardisation. DataBrew recipes are reusable and auditable, suitable for Malta analysts performing data preparation work.

  • Glue Workflows and Orchestration

    We implement AWS Glue Workflows to orchestrate multi-step Malta ETL processes — triggering crawlers, Glue jobs, and Lambda functions in sequence with dependency management. Glue Workflows provide visual pipeline representation and execution monitoring for Malta data engineering teams, replacing the manual scripting of complex multi-step transformation sequences.

/ overview /

Neural AI implements AWS Glue for Malta businesses on Amazon Web Services that need serverless, managed data integration — building ETL pipelines, data catalogues, and data lake transformation workflows without Spark cluster management overhead.

Serverless ETL for Malta AWS Workloads

AWS Glue removes the infrastructure layer from Malta ETL development. Cluster provisioning, Spark configuration, and scaling are handled by AWS; Malta data engineering teams write transformation logic. For intermittent batch ETL workloads — the majority of Malta data integration requirements — this serverless model is cost-effective and operationally simple.

The Gateway to the AWS Data Lake

Glue’s combination of serverless ETL and the Data Catalog makes it the natural entry point for Malta businesses building an AWS data lake. The Catalog’s integration with Athena enables SQL queries on S3 data without loading into a database, and Glue Crawlers keep the catalog current as Malta data evolves. Neural AI implements Glue as part of complete Malta AWS data lake architectures.

Contact us to discuss AWS Glue requirements for your Malta organisation.

/ how it works /

Live in weeks, not months.

01

AWS Data Architecture Assessment

We assess your Malta AWS data sources, targets, and transformation requirements to design the appropriate Glue architecture — job type selection, DPU configuration, and integration with S3 data lake and Redshift.

02

Data Catalog and Crawler Setup

We configure Glue Crawlers for Malta data sources, set up the Data Catalog database structure, and implement crawler schedules for keeping schemas current.

03

ETL Job Development

We develop Glue ETL jobs in PySpark for Malta transformation requirements, using Glue's DynamicFrame abstraction for schema flexibility or converting to DataFrames for standard Spark operations.

04

DataBrew Recipe Development

Where visual data preparation is appropriate for Malta requirements, we implement DataBrew recipes for common data quality transformations, enabling analyst-level maintenance of preparation logic.

05

Workflow and Trigger Configuration

We implement Glue Workflows for multi-step Malta pipelines, configure schedule and event-based triggers, and connect to EventBridge for S3-event-driven pipeline execution.

06

Monitoring and Operations

We configure CloudWatch metrics and alarms for Glue job failures, SLA misses, and DPU cost thresholds for Malta data operations monitoring.

/ what you get /

Everything you need. Nothing you don't.

01

Serverless ETL Pipeline Development

Neural AI builds AWS Glue ETL jobs for Malta businesses — serverless Spark-based data processing that scales automatically without cluster management. Glue jobs process data from S3, RDS, Redshift, DynamoDB, and other AWS sources, applying transformations using Python (PySpark) or Scala. We implement Glue jobs for Malta data engineering requirements — data cleaning, format conversion, schema normalisation, and loading analytical targets — with Glue's automatic worker scaling eliminating capacity planning.

02

AWS Glue Data Catalog

We implement the AWS Glue Data Catalog as the metadata repository for Malta business data lake assets — crawling S3 data lake directories, RDS databases, and Redshift to automatically discover and register tables, schemas, and partitions. The Glue Data Catalog integrates with Athena, Redshift Spectrum, and EMR, providing a unified metadata layer that enables SQL querying across Malta data lake assets without data movement.

03

AWS Glue DataBrew

We use AWS Glue DataBrew for visual data preparation — providing a no-code interface for cleaning, normalising, and transforming Malta business data. DataBrew's 250+ pre-built transformations handle common data quality issues without Spark code: date parsing, string manipulation, outlier handling, and format standardisation. DataBrew recipes are reusable and auditable, suitable for Malta analysts performing data preparation work.

04

Glue Workflows and Orchestration

We implement AWS Glue Workflows to orchestrate multi-step Malta ETL processes — triggering crawlers, Glue jobs, and Lambda functions in sequence with dependency management. Glue Workflows provide visual pipeline representation and execution monitoring for Malta data engineering teams, replacing the manual scripting of complex multi-step transformation sequences.

See what aws glue could do for your business.

Book a free 30-minute consultation with our Malta-based AI team — no obligation, just a clear view of your highest-impact opportunities.

Book a free consultation →
/ questions /

AWS Glue FAQ

What is AWS Glue and what is it used for?
AWS Glue is Amazon's managed ETL service — serverless Spark-based data processing combined with a Data Catalog for metadata management. Malta businesses use it for data lake ETL (transforming S3 data for analytics), data catalog management (making data discoverable for Athena and Redshift queries), and simple orchestration of AWS-native data workflows.
How does AWS Glue compare to Azure Data Factory?
Both are managed ETL services from their respective cloud providers. Glue is serverless Spark-native, suited to Malta businesses on AWS with data lake workloads and S3 as the primary storage layer. ADF offers more connectors (90+), a visual pipeline designer, and tighter integration with Microsoft services. Neural AI recommends Glue for Malta businesses on AWS; ADF for Malta businesses on Azure.
When should Malta businesses use AWS Glue versus EMR or Databricks?
Glue is appropriate for serverless, job-based ETL workloads on AWS where clusters are wasteful. EMR suits Malta workloads needing persistent clusters, fine-grained Spark configuration, or tools unavailable in Glue. Databricks is preferred for Malta businesses needing advanced MLOps, Delta Lake, or Unity Catalog. Glue is the low-overhead choice for intermittent ETL; Databricks for complex unified data and AI platforms.
What is the AWS Glue Data Catalog?
The Glue Data Catalog is a centralised metadata repository that stores table definitions, schemas, and partition information for Malta data lake assets. It integrates with Athena (enabling SQL queries on S3), Redshift Spectrum, and EMR. Glue Crawlers automatically populate the catalog by scanning S3 and databases. It functions as the Hive Metastore for AWS-native analytical services.
How are AWS Glue jobs priced?
Glue ETL jobs are billed per DPU-second (Data Processing Unit) — compute time consumed during job execution. Each DPU is 4 vCPUs and 16 GB memory. A job running 10 DPUs for 10 minutes consumes 100 DPU-minutes. Glue crawlers have separate per-DPU-hour pricing. Neural AI sizes Glue jobs for Malta workloads to balance performance and cost.
Can AWS Glue handle streaming data for Malta businesses?
AWS Glue Streaming ETL jobs process data from Kinesis and Kafka in near-real-time using micro-batching. For Malta businesses with streaming ingestion requirements, Glue Streaming provides a serverless alternative to managing Spark Structured Streaming clusters. For sub-second latency requirements, Lambda or purpose-built streaming tools are more appropriate than Glue.
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