Release Notes: v0.7.0

release-note We are glad to announce the availability of GraphScope v0.7. This release includes major updates for the persistent graph store in GraphScope, providing APIs for real-time graph updates (inserts and deletes of individual vertices and edges). It also focuses on user-friendly improvements, security issues, code quality, and a series of bug fixes.

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Author's profile picture GSTeam@Alibaba on ReleaseNotes

Release Notes: v0.6.0

release-note We are glad to announce the release of GraphScope 0.6. This major release integrates a new graph interactive engine GAIA, which supports efficient parallel execution and bounded-memory execution for Gremlin queries. More technical details of GAIA can refer to our published tech blog. Note that currently the integration of GAIA with GraphScope is experimental, and is not recommended for production use yet! In addition, this release improves the experience of local deployment on MacOS, Ubuntu and CentOS, and adds more graph analytics algorithms.

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Author's profile picture GSTeam@Alibaba on ReleaseNotes

GAIA Deep Dive: Bounded-Memory Execution and Early-Stop Optimization for Efficient Graph Traversal at Scale

knife Last time, we presented an overview of the GAIA engine for scaling Gremlin for large distributed graphs. In contrast to other, existing batch-oriented big graph processing systems, such as Google Pregel, Apache Giraph, GraphLab PowerGraph, and Apache Spark GraphX, GAIA focuses on low-latency graph traversal at scale. Achieving this goal requires a different distributed infrastructure. Today, we continue to explain why with highlighting two unique and key features of GAIA.

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Author's profile picture GSTeam@Alibaba on Tech

Release Notes: v0.5.0

release-note We are glad to announce the GraphScope 0.5 release. As the first step towards the ease of deployment in production, this major release includes two new features, namely a persistent graph store to enable a “service mode” for real-time graph computing, and lazy evaluation of GraphScope programs–an execution strategy which delays the execution of a GraphScope program until later when needed for efficiency. In addition, we improve the compatibility with NetworkX. ​ We highlight the following improvements included in this release: ​

  1. GraphScope-Store: A persistent store for mutable graphs. Currently, it has supported the following features/functions:
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Author's profile picture GSTeam@Alibaba on ReleaseNotes

Towards a Swiss Army Knife for a Continuous Life Cycle of Big Graph Analytics

knife In this post, we will present a high-level road-map of the GraphScope project with highlighting new exciting features coming in the v0.5 release.

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Author's profile picture GSTeam@Alibaba on Tech

Release Notes: v0.4.0

release-note Today, we’re announcing the availability of GraphScope v0.4.0. This release focuses on the compatibility improvement with NetworkX, with the aim of allowing users to develop graph applications on large-scale graphs in a distributed environment just like doing this on a single machine. In addition, this release improves the experience of standalone deployment.

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Author's profile picture GSTeam@Alibaba on ReleaseNotes

Introducing GAIA: A Scalable Engine for Gremlin – the SQL for Graphs

gaia GAIA extends GraphScope with Gremlin, the industry’s de facto standard property graph query language defined and maintained by the Apache TinkerPop project, which is widely adopted by popular graph database vendors such as Neo4j, OrientDB, JanusGraph, Microsoft Cosmos DB, and Amazon Neptune. GAIA is the first open-source implementation of Gremlin in a distributed or big-data environment in the industry.

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Author's profile picture GSTeam@Alibaba on Tech

Release Notes: v0.3.0

release-note GraphScope v0.3.0 is released as scheduled. This release includes new features and major updates for frontend APIs for graph manipulation, integration with other systems as well as code optimization for some operators. Another direction we are working on is to ease the deployment of GraphScope with/without Kubernetes.

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Author's profile picture GSTeam@Alibaba on ReleaseNotes

A Review of Programming Models for Parallel Graph Processing

programing-models To explore underlying insights hidden in graph data, many graph analytics algorithms, e.g., PageRank and single source shortest paths (the Dijkstra’s algorithm), have been designed to solve different problems.

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Author's profile picture GSTeam@Alibaba on Tech

Introducing GraphScope Playground

try-record.gif Today we released GraphScope 0.2.0. With this release, we are happy to introduce GraphScope Playground, a hosted JupyterLab with GraphScope ready out-of-the-box. Now you can get started with GraphScope straight away in your browser without any hassle for setting it up.

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Release Notes: v0.2.0

release-note The GraphScope team is pleased to announce the 0.2.0 release after two-months development. The 0.2.0 release is focused on better getting started experience for end-users and we have make a lot of improvements since the last minor release. We have improved our documentation a lot, and made the kubernetes integration work for more settings. We have also brought the support for various I/O to make GraphScope suitable for more production environments.

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Author's profile picture GSTeam@Alibaba on ReleaseNotes

Say Hello to GraphScope!

graphscope-releasing The source code of GraphScope is released today!

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Author's profile picture GSTeam@Alibaba on Newsroom