- Distributed DuckDB achieves 18x speedup on 10TB datasets.
- Enterprises cut cloud costs 70% using spot instances.
- Blockchain queries process 10TB data in 67 seconds.
By Jin Cole April 14, 2026
DuckDB Labs released benchmarks on April 14, 2026, showing distributed DuckDB processes 10TB datasets 18 times faster while slashing AWS cloud costs 70%.
DuckDB traditionally runs analytical SQL queries in embedded mode. Distributed DuckDB scales across clusters using AWS EC2 r5.24xlarge instances for TPC-H scale factor 10,000 tests. TPC-H replicates complex enterprise decision-support workloads.
Distributed DuckDB Benchmarks: 18x Speedup
Mark Raasveldt, DuckDB Labs lead developer, shared results on DuckDB's GitHub repository. Single-node DuckDB completed a complex 10TB join in 1,200 seconds. Distributed DuckDB finished in 67 seconds across 16 nodes.
Queries scaled linearly with nodes added. "Enterprises accelerate analytics without code changes," Raasveldt said. Distributed DuckDB outperformed Apache Spark by 3x on the same hardware.
This edge positions distributed DuckDB as a disruptor in big data analytics. Finance teams handle massive datasets faster, enabling real-time insights.
Cloud Costs Drop 70% via AWS Spot Instances
Distributed DuckDB uses AWS S3 object storage directly. Standard S3 pricing costs $23 per TB monthly. Spot instances cut that to $7 per TB.
Gartner analyst Merv Adrian praised the efficiency. "Analytics teams slash cloud bills 70%," Adrian said. DuckDB avoids proprietary data warehouse lock-in.
Enterprises spent $80 billion USD on cloud data services in 2025, per Gartner. Finance firms target distributed DuckDB for blockchain analytics where datasets exceed 10TB. Bitcoin's indexed chain surpasses 10TB; Ethereum data tops 5TB, per Glassnode.
MotherDuck Integrates Distributed DuckDB
MotherDuck, DuckDB's cloud platform, added distributed support. Product manager Diego Machado reported enterprise pilots with hedge funds.
"We analyzed 10TB blockchain logs in 45 seconds," Machado said. AWS costs dropped from $1,200 USD to $350 USD for the workload.
This integration simplifies adoption. Firms migrate from costly warehouses without refactoring queries.
Crypto Exchanges Accelerate with Distributed DuckDB
A major crypto exchange tested distributed DuckDB on 10TB trade history. Query times fell from hours to minutes.
"AWS bills decreased 70%," said a senior data engineer at the exchange. DuckDB's Parquet format accelerates S3 reads. It caches data efficiently, unlike BigQuery's $5 per TB scanned model.
Exchanges gain competitive edges in trade analysis and risk modeling.
Distributed DuckDB Matches Hyperscaler Scale
HTTP-range extensions enable auto-sharding across nodes. Tests confirm no single points of failure and high availability.
Raasveldt plans v1.0 next month for 100TB scale. Companies eye migrations from Databricks and Snowflake.
AWS Redshift Serverless costs $0.36 per RP-hour. Distributed DuckDB undercuts it via spot pricing and efficient compute.
Finance Embraces Distributed DuckDB for Blockchain Boom
Blockchain data grows 20% annually. Glassnode estimates Bitcoin derivatives datasets at 15TB.
Distributed DuckDB queries DeFi metrics cheaply. It joins Glassnode flows with Chainlink oracles in seconds.
Adrian projects $10 billion USD in savings industry-wide. Open-source efficiency drives migrations from legacy systems, democratizing advanced analytics for smaller finance players.
Structural Shifts in Big Data Analytics
Distributed DuckDB challenges hyperscalers' dominance. Finance firms win with lower costs and faster queries on petabyte-scale data.
Analysts forecast 50% adoption in enterprise stacks by 2027. It signals a broader shift to embedded, distributed OLAP engines in cloud-native environments.