Parallel Computing For
Extreme Performance Data Analytics

Bodo is the platform to take your Python and SQL data analytics code directly to production with extreme performance and massive scaling through automatic under-the-hood parallelization.

Get Started

@bodo.jit
def data_transform():
  df = pd.read_parquet(input_parquet_file)
  df["B"] = df.apply(lambda r: "P1" if r.A.month < 5 else "P2", axis=1) 
  df["C"] = df.A.dt.month 
  df.to_parquet(output_parquet_file)

Run Regular Python / SQL at Supercomputing Scale

Go from prototype to production with no change to your code. No need to use PySpark, rewrite in Scala, or use costly platforms to achieve performance. No new libraries or APIs to learn. And it's simpler than Spark, all with painless One-Click scaling.

Simplicity

Your code is quickly production ready, with one-click to scale from a laptop

Scale

Linearly scale your python code from a laptop to 10,000’s of cores

Speed

Get up to 100X speedup over alternative solutions at massive scale

Savings

Efficient parallel execution provides up to 10X increased resource efficiency

+10,000

Cores with no code changes to your code on your laptop

TECHNOLOGY

10x

Faster than Spark, Dask, or Ray—with linear performance scaling

BENCHMARKS

90%+

Reduced compute infrastructure cost with improved resource efficiency

ECONOMICS

Use Bodo with Popular Data Tools

Bodo is completely compatible with popular platforms, data warehouses, and lakehouses. You can source your data with parallel I/O and deploy on any compute infrastructure of your choice.

Open Source APIs