Apache Giraph
Apache Giraph is an iterative graph processing system built for high scalability on Apache Hadoop. It is modeled after Google's Pregel and provides a simple yet flexible Java API for graph algorithms at massive scale using the Bulk Synchronous Parallel (BSP) model. Note - Apache Giraph has been retired as of 2024.
Apache Giraph publishes 2 APIs on the APIs.io network: Cluster API and Job Management API. Tagged areas include Apache, Big Data, BSP, Graph Processing, and Hadoop.
The Apache Giraph catalog on APIs.io includes 1 JSON-LD context and 2 Spectral governance rulesets.
Apache Giraph’s developer surface includes documentation, getting-started guide, and 7 more developer resources.
Kin Score
APIs 3
Individual APIs this provider publishes, each with its own machine-readable definition.
Apache Giraph Java API
Java API based on the Bulk Synchronous Parallel (BSP) model for implementing graph algorithms, with Vertex, Edge, and Master compute APIs for distributed graph processing on Had...
Apache Giraph Cluster API
The Cluster API from Apache Giraph — 1 operation(s) for cluster.
Apache Giraph Job Management API
The Job Management API from Apache Giraph — 2 operation(s) for job management.
Open Collections 1
Open, tool-agnostic API collections (OpenAPI-derived and Bruno).
Apache Giraph Job Monitoring API
OPEN COLLECTIONPricing Plans 1
Published pricing tiers and plan structures.
Rate Limits 1
Documented rate limits and quota policies.
Apache Giraph Rate Limits
RATE LIMITSFinOps 1
Cost, billing, and metering signals for API financial operations.
Apache Giraph Finops
FINOPSFeatures 8
Notable capabilities this provider offers.
Bulk Synchronous Parallel (BSP) Model
Google Pregel-inspired BSP computation model where vertices communicate through supersteps.
Vertex-Centric Programming
Write graph algorithms by defining per-vertex compute functions that exchange messages with neighbors.
Master Compute API
Global coordination API for aggregating results and controlling algorithm termination across supersteps.
Aggregators
Sharded aggregators for collecting global statistics across all vertices during computation.
Edge-Oriented Input
Flexible input formats for loading graphs from HDFS, Hive, Gora, and Rexster sources.
Out-of-Core Computation
Spill graph data to disk for processing graphs larger than available memory.
Hadoop Integration
Runs as a MapReduce job on Apache Hadoop YARN for resource management and fault tolerance.
Fault Tolerance
Checkpoint-based recovery for fault tolerance across superstep boundaries.
Scroll for all 8
Semantic Vocabularies 1
JSON-LD contexts and semantic vocabularies used across these APIs.
Apache Giraph Job Context
JSON-LDSpectral Rules 2
Spectral governance rulesets for linting and validating these APIs.
Apache Giraph API Rules
SPECTRALApache Giraph API Rules
SPECTRALJSON Schema 4
Standalone JSON Schema definitions for this provider's data models.
ApplicationInfo
JSON SCHEMAApplicationResponse
JSON SCHEMAApplicationsResponse
JSON SCHEMAClusterMetricsResponse
JSON SCHEMAJSON Structure 4
JSON Structure definitions describing this provider's data shapes.
Giraph Job Application Info Structure
JSON STRUCTUREGiraph Job Application Response Structure
JSON STRUCTUREGiraph Job Applications Response Structure
JSON STRUCTUREGiraph Job Cluster Metrics Response Structure
JSON STRUCTUREExamples 4
Example request and response payloads for these APIs.
Security Posture 2
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Agentic Access 1
Recommended x-agentic-access execution contracts for AI agents.
Use Cases 5
What developers build with this provider.
Social Graph Analysis
Analyze social network connections, communities, and influence at billions-of-vertices scale (as used at Facebook).
PageRank Computation
Compute web page or entity rankings using iterative link analysis algorithms.
Shortest Path Computation
Find shortest paths between vertices for network routing and recommendation problems.
Connected Components
Identify clusters and connected components in large graphs for community detection.
Graph Machine Learning Features
Generate graph-structural features for machine learning models at scale.
Integrations 5
Pre-built integrations with other platforms and tools.
Apache Hadoop
Runs on Hadoop YARN as a MapReduce application for cluster resource management.
Apache Hive
Hive I/O module for loading graph data from Hive tables.
Apache Gora
Gora I/O module for loading graph data from various NoSQL data stores.
Rexster
Rexster graph server I/O module for loading data from TinkerPop graph databases.
Apache HBase
HBase integration for storing and loading vertex and edge data.
Resources
Get Started 1
Portal, sign-up, and the first successful call
Documentation 1
Reference material describing how the API behaves
Agent Surfaces 1
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 2
Pagination, idempotency, versioning, errors, and events
Build 2
SDKs, sample code, and the tooling you integrate with
Access & Security 2
Authentication, authorization, and security posture