Recallgraph Lifetime Deal $29.00

A time-dependent graph is, informally speaking, a graph structure dynamically changes with time. In such graphs, the weights associated with edges dynamically change over time, that is, the edges in such graphs are activated by sequences of time-dependent elements. Many real-life scenarios can be better modeled by time-dependent graphs, such as bioinformatics networks, transportation networks, and social networks.

In particular, the time-dependent graph is a very broad concept, which is reflected in the related research with many names, including temporal graphs, evolving graphs, time-varying graphs, historical graphs, and so on. Though static graphs have been extensively studied, for their time-dependent generalizations, we are still far from a complete and mature theory of models and algorithms. 

RecallGraph is a versioned-graph data store – it retains all changes that its data (vertices and edges) have gone through to reach their current state.

It supports point-in-time graph traversals, letting the user query any past state of the graph just as easily as the present.

RecallGraph is a potential fit for scenarios where data is best represented as a network of vertices and edges (i.e., a graph) having the following characteristics:

1. Both vertices and edges can hold properties in the form of attribute/value pairs (equivalent to JSON objects).
2. Documents (vertices/edges) mutate within their lifespan (both in their individual attributes/values and in their relations with each other).
3. Past states of documents are as important as their present, necessitating retention and queryability of their change history

ACID Transactions
All write operations are wrapped in ACID-compliant transactions, so your data is always consistent.

REST API
Access all functionality through REST API endpoints. Integrate into any stack. Call the API from anywhere, including servers and browsers.

Recoverable Deletes, Purge, Import and more…
Any data that you delete can always be restored, unless its history is explicitly purged from the database. You can also import your existing non-temporal data and begin tracking revisions from there.

Point-in-Time
Travel back in time to view individual node/edges states from the past, or run graph traversals or shortest-path queries on historical graph states.

Distributed Tracing Support
RecallGraph is an OpenTracing-compliant service. Plug into your existing distributed tracing infrastructure and get insights and performance metrics OOTB.

Extensive Documentation
Well designed documentation to familiarize you with the core concepts and get you up and running in the shortest time possible.

API Features

RecallGraph’s API is split into 3 top-level categories:

Document

• Create – Create single/multiple documents (vertices/edges).
• Replace – Replace entire single/multiple documents with new content.
• Delete – Delete single/multiple documents.
• Update – Add/Update specific fields in single/multiple documents.
• Restore – Restore deleted nodes back to their last known undeleted state.
• (Planned) Materialization – Point-in-time checkouts.
• (Planned) CQRS/ES Operation Mode – Async implicit commits.

Event

• Log – Fetch a log of events (commits) for a given path pattern (path determines scope of documents to pick). The log can be optionally grouped/sorted/sliced within a specified time interval.
• Diff – Fetch a list of forward or reverse commands (diffs) between commits for specified documents.
• Explicit Commits – Commit a document’s changes separately, after it has been written to DB via other means (AQL / Core REST API / Client).
• (Planned) Branch/Tag – Create parallel versions of history, branching off from a specific event point of the main timeline. Also, tag specific points in branch+time for convenient future reference.

History

• Show – Fetch a set of documents, optionally grouped/sorted/sliced, that match a given path pattern, at a given point in time.
• Filter – In addition to a path pattern like in ‘Show’, apply an expression-based, simple/compound post-filter on the retrieved documents.
• Traverse – A point-in-time traversal (walk) of a past version of the graph, with the option to apply additional post-filters to the result.
• k Shortest Paths – Point-in-time, weighted, shortest paths between two endpoints.
• Purge – Delete all history for specified nodes.