The Warehouse That Lives in Your AWS
Amazon Redshift is a columnar, massively parallel data warehouse built for analytics on petabytes. Its real advantage is gravity: if your data already lands in S3 and your apps already run on AWS, Redshift is the shortest path from raw events to a dashboard.
It rewards good design more than most platforms. Distribution keys, sort keys and workload management are the difference between a cluster that answers instantly and one that crawls — which is where most of our engagements start.
Native to Your AWS Estate
S3, Glue, Kinesis, IAM and VPC all wire together with no third-party connectors in the middle.
Columnar & Parallel
Compressed column storage across many nodes — analytical scans read only what they need.
Predictable Economics
Reserved capacity and Serverless both available — pick a fixed bill or a usage-based one.
Engineered for AWS Analytics
The capabilities that make Redshift the default warehouse for AWS-native teams.
Columnar MPP Engine
Compressed columns spread across nodes — scans touch a fraction of the bytes a row store would.
Redshift Spectrum
Query exabytes sitting in S3 directly, without loading them into the cluster first.
Redshift Serverless
Skip cluster sizing entirely and pay only for the capacity your queries actually consume.
Workload Management
Queues and concurrency scaling keep the CEO's dashboard fast while a big ETL job runs.
Redshift ML
Train and invoke SageMaker models from SQL — predictions without a separate pipeline.
VPC & IAM Security
Private networking, KMS encryption and IAM roles — it inherits the controls you already run.
End-to-End Redshift Services
From cluster design to the queries that were quietly costing you a fortune.
Cluster & Schema Design
Distribution keys, sort keys and node sizing chosen for how your queries actually run.
Migration
Move from on-prem Oracle, Teradata or SQL Server onto Redshift with validated parity.
AWS Glue & S3 ETL
Ingestion from S3, Kinesis and RDS - AI drafts the Glue jobs and data-quality tests, a developer reviews them before data lands on schedule.
Performance Tuning
Vacuum, analyze, WLM tuning and query rewrites for clusters that have slowly gone bad.
Cost Optimisation
Right-sizing, reserved nodes vs Serverless, and killing the scans nobody knew were running.
BI Integration
QuickSight, Power BI and Tableau connected to a modelled layer the business trusts.
Distribution and Sort Keys Done Properly
Redshift spreads every table across compute slices. How rows are distributed decides whether a join runs locally on each slice or has to shuffle data across the network, and that shuffle is the most common reason a query that should take seconds takes minutes.
We review the query history (system tables and the query profile) before changing anything, so every key choice is backed by how the warehouse is really used, not by guesswork. Automatic table optimisation is a useful starting point, but it cannot see the joins you plan to add next quarter.
Distribution style
KEY distribution on the shared join column for large fact and dimension pairs, ALL for small, slowly changing dimensions, and EVEN or AUTO where no join dominates. We check for skew so no single slice does most of the work.
Sort keys and zone maps
A sort key on the column you filter by most, usually a timestamp, lets Redshift skip blocks it does not need. Compound keys suit predictable filters; we avoid interleaved keys unless the access pattern really justifies their maintenance cost.
Compression and maintenance
Column encodings, materialized views for repeated aggregations, and vacuum and analyze routines that keep statistics fresh after large loads.
Serverless, RA3 or the Data Lake?
Redshift now comes in several shapes. Choosing the right one matters more for your bill than any single query fix.
Provisioned RA3 clusters
RA3 nodes separate compute from Redshift Managed Storage, so you size the cluster for query load rather than data volume. A good fit for steady, busy workloads where reserved capacity gives a predictable monthly bill, plus data sharing between clusters.
Redshift Serverless
Capacity scales automatically and you pay for compute while queries run. Ideal for intermittent, spiky or new workloads. We set base capacity, usage limits and query monitoring rules so a runaway job cannot quietly run up the bill.
Spectrum and the S3 lake
Keep hot data in Redshift and cold or raw history in S3 as partitioned Parquet, catalogued in AWS Glue and queried through Spectrum. You stop paying warehouse storage for data that is read once a quarter.
A Migration Plan You Can Verify
Moving onto Redshift from Oracle, Teradata, SQL Server or PostgreSQL means converting schemas and stored procedures (the AWS Schema Conversion Tool helps with the first pass), bulk-loading history from S3 with COPY, and running both systems in parallel while row counts and key reports are reconciled.
We also help teams move off Redshift when another platform fits better, for example to BigQuery or Snowflake, by unloading to open Parquet files in S3 so the data is never locked in.
- Pause or resize idle clusters - dev and test warehouses rarely need to run overnight.
- Watch concurrency scaling and Spectrum scans - both are useful and both are billed separately.
- Find the expensive queries - a handful of unfiltered dashboard queries often account for most of the load.
- Clear commercial terms - transparent, milestone-based pricing, an NDA before kickoff, and you own all code and IP. We reply to every inquiry within 24 hours.
Pixel-perfect software, delivered at AI speed
PixoBots stands for Pixel & Bots. Our Bots are dedicated developers who work with AI tools: AI takes the repetitive work, a developer reviews every line, and the result is pixel-perfect.
Pixel
Polished UI and clean, tested code - detail is part of the job, not an afterthought.
Bots
Dedicated developers who join your team and use AI for boilerplate, tests and documentation.
Savings
AI-assisted delivery can save more than 50% of development cost compared with traditional development.
Ready to Get More From Redshift?
Whether you're migrating in or rescuing a cluster that's slowed to a crawl, our engineers can help.