4 Repos
Running SQL queries against petabytes of data stored in HDFS and cloud storage for batch analytics.
Distinct from Data Warehousing: Distinct from Data Warehousing: specifically targets Hadoop and cloud storage backends, not traditional MPP or cloud-native warehouses.
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Apache Hive is a SQL-on-Hadoop data warehouse that enables querying and managing petabytes of data stored in distributed storage such as HDFS and cloud storage services. It provides a familiar SQL interface for batch analytics and reporting, supported by a core set of components including the HiveServer2 Thrift service for remote query execution, the Hive Metastore Service for central metadata management, the Hive ACID Transaction Engine for concurrent read-write operations, and the Hive LLAP Interactive Engine for low-latency analytical processing. The WebHCat REST API offers an HTTP interfac
Provides a SQL-on-Hadoop data warehouse for querying petabytes of distributed data.
JanusGraph is a distributed, elastically scalable graph database designed to store and query highly connected data across a cluster of machines. It supports the property graph data model with ACID consistency and integrates multi-model search capabilities including geo, numeric range, and full-text queries. The database also includes a Graph OLAP engine for running batch analytics and global graph computations on large datasets using the Hadoop framework. The project distinguishes itself through a masterless cluster architecture that eliminates single points of failure, allowing every node to
Runs full-graph processing jobs as MapReduce or Spark tasks on a Hadoop cluster for offline computation.
HBase ist ein verteilter, Wide-Column-NoSQL-Speicher und Big-Data-Speicher-Engine, die für spärliche Datensätze konzipiert ist. Sie fungiert als skalierbare spaltenorientierte Datenbank, die auf dem Hadoop Distributed File System aufbaut, um Echtzeit-Lese- und Schreibzugriffe auf massive Mengen strukturierter und unstrukturierter Daten zu ermöglichen. Das System agiert als sprachübergreifendes Datenbank-Gateway und bietet Konnektivität über native Remote Procedure Calls (RPC), REST- und Thrift-Schnittstellen. Es zeichnet sich durch ein Master-Worker-Koordinationsmodell aus, das horizontale Skalierung und Fehlertoleranz über einen Cluster hinweg ermöglicht. Das Projekt deckt ein breites Spektrum an Funktionen ab, einschließlich fein abgestimmter Zugriffskontrolle über Visibility-Labels auf Zellebene, plugbarer Datenkompression und serverseitiger Datenaggregation. Es unterstützt zudem Big-Data-Analytics-Workflows durch Map-Reduce-Integration und erlaubt die Ausführung benutzerdefinierter serverseitiger Logik. Die betriebliche Überwachung wird durch System-Metrik-Tracking und Plugin-basierten Metrik-Export bereitgestellt.
Implements a distributed NoSQL wide-column store built on top of the Hadoop ecosystem for sparse datasets.
Kylin is a distributed OLAP engine designed for executing fast SQL queries on massive datasets. It utilizes multi-dimensional data cubes to pre-calculate data aggregates, enabling sub-second response times for large-scale analytical queries and big data analytics. The system focuses on large-scale data warehousing and multi-dimensional data modeling. It allows for the organization and querying of vast amounts of structured data to support business intelligence and reporting workflows through distributed SQL querying.
Persists massive datasets and pre-computed cubes on the Hadoop distributed file system for scalability.