Whether you’re a student or a seasoned research professional, we have a package designed to suit your needs:

  • Stata/MP: The fastest edition of Stata (for quad-core, dual-core, and multicore/multiprocessor computers) that can analyze the most data
  • Stata/SE: Stata for large datasets
  • Stata/IC: Stata for mid-sized datasets
  • Numerics by Stata: Stata for embedded and web applications

Stata/MP is the fastest and largest version of Stata. Virtually any current computer can take advantage of the advanced multiprocessing of Stata/MP. This includes the Intel i3, i5, i7, i9, Xeon, Celeron, and AMD multi-core chips. On dual-core chips, Stata/MP runs 40% faster overall and 72% faster where it matters, on the time-consuming estimation commands. With more than two cores or processors, Stata/MP is even faster. Find out more about Stata/MP.

Stata/MP, Stata/SE, and Stata/IC all run on any machine, but Stata/MP runs faster. You can purchase a Stata/MP license for up to the number of cores on your machine (maximum is 64). For example, if your machine has eight cores, you can purchase a Stata/MP license for eight cores, four cores, or two cores.

Stata/MP can also analyze more data than any other edition of Stata. Stata/MP can analyze 10 to 20 billion observations given the current largest computers, and is ready to analyze up to 1 trillion observations once computer hardware catches up.

Stata/SE and Stata/IC differ only in the dataset size that each can analyze. Stata/SE (up to 10,998) and Stata/MP (up to 65,532) can fit models with more independent variables than Stata/IC (up to 798). Stata/SE can analyze up to 2 billion observations.

Stata/IC allows datasets with as many as 2,048 variables and 2 billion observations. Stata/IC can have at most 798 independent variables in a model.

Numerics by Stata can support any of the data sizes listed above in an embedded environment.

All the above edition have the same complete set of features and include PDF documentation.

Product features

Stata/IC

Stata/SE

Stata/MP

Maximum number of variables

 

2,048 32,767  120,000

Maximum number of observations

 

2.14 billion 2.14 billion  Up to 20 billion

Maximum number of independent variables

 

798 10,998 65,532

Multicore support

Time to run logistic regression with 10 million observations and 20 covariates

 

1-core

20 sec

1-core

20 sec

2-core

10 sec

4-core

5.2 sec

6+

<5.2 sec

Complete suite of statistical features

 

Publication-quality graphics

 

Matrix programming language

 

Complete PDF documentation

 

Exceptional technical support

 

Includes within-release updates

 

64-bit version available

 

Disk space requirements 1 GB 1 GB 1 GB
Memory space requirements 1 GB 2 GB 4 GB