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使用 Homebrew, Nix 安装 hbase

查看 hbase 的安装路径、可执行文件、元数据以及面向 AI 代理工作流的安全说明。

安装

其他安装命令

macOS

Homebrew已验证 · 100%
brew install hbase

local Homebrew formula metadata

概览

软件包摘要

Hadoop database: a distributed, scalable, big data store

命令和别名

  • hbase
  • start-hbase.sh
  • stop-hbase.sh

历史

项目历史与用法

Apache HBase is a distributed, scalable, Bigtable-like data store built on Hadoop and HDFS for random, real-time read/write access to very large sparse tables. In package-manager terms it is a heavyweight data-system package: a CLI, daemons, configuration directory, Java/Hadoop dependency stack, and operational database all in one.

项目历史

The official reference guide's history appendix begins with Google's 2006 Bigtable paper, then places the start of HBase development at the end of 2006. The project was designed to bring Bigtable-like capabilities to the Hadoop ecosystem rather than to be a standalone relational database.

HBase became a Hadoop sub-project in 2008 and an Apache top-level project in 2010. That transition matters historically because it moved HBase from an add-on in the Hadoop orbit to an Apache project with its own project management committee, release process, community, and operational identity.

The HBase website describes the system as a distributed, scalable big-data store for random, real-time read/write access. It emphasizes billions of rows, millions of columns, consistent operations, automatic failover and sharding on Hadoop/HDFS, and APIs including Java, REST, Thrift, filters, and Bloom filters.

The reference guide is unusually central to the project history: it covers standalone quick starts, distributed modes, configuration files, shell usage, schema design, MapReduce integration, security, architecture, backup/restore, replication, APIs, performance tuning, operations, and development. That breadth reflects HBase's evolution from a storage engine into a production database system with a large operator surface.

采用历史

The official Powered by Apache HBase page lists user-submitted deployments across companies, institutions, and projects. It includes early production or large-scale use cases from Adobe, Facebook Messages, Flurry, HubSpot, OCLC WorldCat, OpenLogic, Trend Micro, Twitter, WorldLingo, Yahoo, and others.

The adoption examples show why HBase became important in the Hadoop era: teams needed low-latency reads and updates, wide sparse rows, time-series or event data, search and analytics backends, and MapReduce/Spark-adjacent processing without abandoning the commodity-cluster model.

HBase's adoption was also ecosystem-driven. Its value came not only from the database itself, but from living near HDFS, Hadoop MapReduce, ZooKeeper, Java clients, REST/Thrift gateways, and later higher-level systems such as Trafodion or Spark integrations.

使用方式

The quick start uses a standalone instance where the Master, RegionServer, and ZooKeeper daemon run in one JVM, then connects through the hbase shell to create, list, describe, put, and scan a table. Production usage moves the same model into distributed deployments with separate daemons and HDFS storage.

Administrators configure HBase through files such as conf/hbase-site.xml and conf/hbase-env.sh, start and stop services with scripts such as start-hbase.sh and stop-hbase.sh, and use the shell, Java API, REST, Thrift, MapReduce jobs, and operational tools to manage data and clusters.

为什么软件包爱好者会关心

HBase is a classic package-manager stress test because installing the package is only the beginning. The formula has to deliver shell commands and scripts, but the real system depends on Java compatibility, Hadoop/HDFS behavior, ZooKeeper coordination, configuration files, daemon management, and careful version matching.

For package nerds, HBase also represents the Hadoop-era pattern where a local package can be used for development or a single-node quick start, while production meaning lives in clusters, configuration, and service orchestration. That makes its package metadata deceptively small compared with its operational footprint.

时间线

  • 2006: Google publishes the Bigtable paper.
  • 2006: HBase development starts near the end of the year.
  • 2008: HBase becomes a Hadoop sub-project.
  • 2010: HBase becomes an Apache top-level project.
  • 2020s: The official site continues to present HBase as a top-level Apache project and Bigtable-like Hadoop database.

Related projects

  • Google Bigtable is the direct design reference named by the HBase documentation.
  • Apache Hadoop, HDFS, ZooKeeper, MapReduce, Spark, REST, Thrift, and Apache Trafodion are related technologies in the official documentation and adoption pages.
  • HBase's source repository is managed by Apache through Git/GitBox.

安全态势

风险级别:orange

broad file, network, media, or database tool signal. formula declares a Homebrew service.

风险分类器

orange 风险 · 中 置信度 · infrastructure

原因

  • broad file, network, media, or database tool signal
  • formula declares a Homebrew service

信号

  • metadata:service
  • text:database

安装行为

  • 未记录 Homebrew bottle 元数据。

建议审查

在无人值守的代理使用前,请检查该工具是否读取明文凭据、写入远程状态、发布制品或调用插件。

local files

Configuration and credential file locations

These source-backed paths show where this package keeps local settings or durable credentials. Automic Vault can use them as review targets for secret scanning, migration, and command approval.

Configuration files

Config paths the tool may read or write during local use.

Unix
conf/hbase-site.xmlconf/hbase-env.sh

可执行文件

已安装的可执行文件

命令类型暴露范围备注
hbase可执行文件已索引可执行文件从本地可执行文件索引发现。
start-hbase.sh可执行文件已索引可执行文件从本地可执行文件索引发现。
stop-hbase.sh可执行文件已索引可执行文件从本地可执行文件索引发现。

新鲜度

版本和新鲜度

这些信号区分页生成时间、软件包管理器活动和上游发布比较。只有存在证据 URL 和可比较版本时,才会提示版本落后。

页面生成时间2026-08-03
管理器版本2.6.6
管理器更新时间2026-07-10
本地数据未知
上游不可用
检测到的最新版本未检测到
  • OK没有生成新鲜度警告。

安装元数据

软件包元数据

软件包键brew:hbase
版本2.6.6
软件包管理器Homebrew
主页https://hbase.apache.org
最后更新2026-07-10T14:07:28Z
Pulseupdated
Bottle未记录
服务未声明

源数据库匹配

其他软件包管理器记录

匹配项来自外部软件包管理器索引,并与本地 Automic Vault 软件包链接分开显示。

Nix95%

hbase

nix profile install nixpkgs#hbase
  • normalized package name match
  • 匹配方式:Hbase
nixpkgs package indexes · raw.githubusercontent.com · nixpkgs package indexes: hbase from https://raw.githubusercontent.com/NixOS/nixpkgs/master/pkgs/top-level/all-packages.nix

来源线索

由仓库数据生成

此页面由 av-webscripts/generate-pkg-sqlite.py 生成的私有软件包 SQLite 工件提供。

使用的来源

  • Geiger risk classifier
  • cross-ecosystem install command graph
  • curated configuration and credential file locations
  • curated package history
  • external package-manager database matches
  • pkg.so package database
  • pkgdb category and tag curation