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vmware-archive/differential-datalog

DDlog is a programming language for incremental computation. It is well suited for writing programs that continuously update their output in response to input changes. A DDlog programmer does not write incremental algorithms; instead they specify the desired input-output mapping in a declarative manner. observed · 2026-08-28

github.com/vmware-archive/differential-datalog · Java · MIT (permissive) · archived observed · 2026-08-28

Health v2 · maintenance only

10/100

  • Activity 0
  • Release rhythm 8
  • Longevity 100

Flags: archived

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 3088
  • days_rel: n/a
  • days_push: 1153
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

1501 stars · 135 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

DDlog is a programming language and compiler for incremental computation, based on a dialect of Datalog and differential dataflow. Programmers declare input-output mappings declaratively, and the compiler synthesizes efficient Rust implementations that continuously update outputs in response to streaming input changes.

Use cases

  • maintain derived results incrementally as input relations change
  • build real-time analytics over streaming relational updates
  • implement static program analysis tools
  • write declarative rules for cloud management systems
  • compute all derived facts bottom-up from input relations
  • process insert/delete/modify updates with minimal recomputation

When to choose

  • your application continuously updates outputs in response to input changes
  • you want declarative relational rules without writing incremental algorithms
  • you need bottom-up computation of all derived facts
  • you work with relational data streams and want amortized performance

When to avoid

  • you need ad-hoc top-down queries rather than maintaining all derived facts
  • your data does not fit in memory
  • you need a general-purpose programming language rather than a declarative DSL
  • you require active community maintenance - the repo is archived

Facets

library · maturity maintenance

programming-language compiler interpreter programming-languages developer-tools rust windows cli datalog incremental-computation differential-dataflow declarative dataflow relational algorithms data-engineering linux macos

1 source

Member repositories

RepositoryRoleHealth v2
vmware-archive/differential-datalogmain10

For agents

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Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem