21 個最好的免費開源數據庫
作為一名開發人員或DBA，您必須使用一些如MS SQL Server，MySQL，Oracle，PostgreSQL，MongoDB等廣泛使用的數據庫。MySQL是目前使用的最好的免費的開源數據庫，大家都知道。但除了MySQL，還有很多你可能不知道或從未使用自由和開放源碼的數據庫。如：PostgreSQL, MongoDB, HBase, Cassandra, Couchbase, Neo4j, Riak, Redis, Firebird等。
1. MySQL
The most widely
used open source database for Web apps (and many other things) remains
MySQL. Support for multiple storage engines, clustering, full-text
indexing, and plenty of other professional features have allowed
numerous other apps profiled here, from WordPress to Movable Type, to
rely on MySQL as their default database. Graphical front ends, such as
phpMyAdmin and Adminer, make using the database far less of a chore. And
for those seeking escape from the long shadow of Oracle, there's a
community fork named MariaDB, maintained by MySQL's original lead
developer, Monty Widenius.
2. PostgreSQL
When Oracle
acquired MySQL, reduced the development staff, and more or less killed
the open source nature of the project, it reopened a market that MySQL
had locked down. PostgreSQL has a much nicer set of drivers and supports
both standard ANSI-SQL and extended features, in many cases better than
MySQL. On the downside, its long legacy has left it multiprocess in the
era of multithreaded. The high-availability/clustering features of
PostgreSQL require a lot of elbow grease and leave much to be desired.
Yet while organizations look for a community developed database, one of
the eldest starts to look pretty good. Many cloud providers, such as
Heroku, have chosen PostgreSQL as their RDBMS storage option as well.
3. MongoDB
NoSQL? Document
database? The first name that comes to mind is MongoDB, due to a
dual-edged blade from developer 10gen. On one side, MongoDB has strong
venture capital and consequently an extensive marketing strategy. On the
other side, it is the only comparatively mature document database in
the NoSQL world. Highly scalable horizontally with automated sharding
and highly available due to autoreplication, MongoDB offers a very
reliable and yet simple solution to modern document database problems.
The downsides: Working with stored procedures can be difficult, and
performing data manipulation can require writing complex JavaScript
code.
4. Hadoop (HBase)
Hadoop is the
name brand in big data. It is also the convergence of "clustered
storage" systems like Gluster and Ceph with NoSQL. Hadoop is really a
collection of projects to solve large and complex data problems. In
fact, there are multiple types of databases and query languages built on
the overall Hadoop framework. Hadoop's complexity is as legendary as
its capability, and its lack of high-availability features has both held
it back and created a commercial add-on ecosystem.
The project
aims to host very large tables like "billions of rows, millions of
columns". It has a REST-ful web service gateway that supports XML,
Protobuf, and binary data encoding options.
5. Apache Cassandra
Written in
Java, this BigTable-based key-value database is getting more popular by
the day. Open source and built to integrate with Hadoop, Cassandra
offers the column family solution to developers wanting to move away
from the relational database model while working with Hadoop. Focusing
mainly on getting in very fast writes and providing high availability,
Cassandra has slower reads than some alternatives. It is mostly used for
logging purposes and real-time analysis.
Cassandra is a
highly scalable second-generation distributed database that is used by
giants like 非死book, Digg, 推ter, Cisco & more. It aims to
provide a consistent, fault-tolerant & highly available environment
for storing data.
6. Couchbase
While Couchbase
was a fork of CouchDB, it has become more of a full-fledged data
product and less of a ball of framework than CouchDB. Its transition to a
document database will give MongoDB a run for its money. It is
multithreaded per node, which can be a major scalability benefit --
especially when hosted on custom or bare-metal hardware. With some nice
integration features, including with Hadoop, Couchbase is a great choice
for an operational data store.
7. Neo4j
The database
for interconnected data, Neo4j provides a reliable Java-based platform
for conquering highly interconnected database problems. Available with
full ACID transaction compatibility -- rare in a NoSQL database -- Neo4j
has a SQL-like query language called Cypher and a scripting language
called Gremlin for graph traversals. Best used to accurately and
efficiently model highly complex, interconnected networks like network
topologies, social networks, and conditional access control problems, it
provides indexes on nodes and relationships. Direct path calculations
take hundreds of lines of code for a RDBMS but two lines of code for
Neo4j.
8. Riak
An open source
distributed database written in Erlang and C, Riak treats all nodes
equally. No one is a master or a slave. Thus, there is no fear a master
will be a single point of failure. However, the masterless, fully
distributed model with SNMP monitoring is not available in the open
source version. Much simpler than its peers (such as Cassandra), Riak is
optimal for places where even seconds of downtime would hurt.
9. Redis
There are many
NoSQL databases, but Redis remains close to our heart because it has so
many features that some call it a "data structure store." You don't just
store numbers and strings -- you can dump in entire hashes, lists,
sets, and other complicated structures. Then, to make the deal sweeter,
Redis offers replication and persistence.
Redis is an
advanced fast key-value database written in C which can be used like
memcached, in front of a traditional database, or on its own. It has
support for many programming languages & used by popular projects
like GitHub or Engine Yard. There is also a PHP client named Rediska for
managing Redis databases.
10. Firebird
Firebird is a
relational database that can run on Linux, Windows & various UNIX
platforms. It offers high performance and powerful language support for
stored procedures and triggers.
11. Memcached
Memcached is an
in-memory key-value store for small chunks of arbitrary data (strings,
objects) from results of database calls, API calls, or page rendering.
It is intended for use in speeding up dynamic web applications by
alleviating database load.
12. Oracle Berkeley DB
It is an
embeddable database engine that provides developers with fast, reliable,
local persistence with zero administration. Oracle Berkeley DB is a
library that links directly into your application & enables you to
make simple function calls rather than sending messages to a remote
server for a better performance.
13. Hypertable
Hypertable is a
high performance distributed data storage system designed to support
applications requiring maximum performance, scalability, and
reliability. It is modeled after Google's BigTable and mostly focuses on
large-scale datasets.
14. Keyspace
It is a
consistently replicated, fault-tolerant key-value store that works in
Windows OS. Keyspace offers high availability by masking server/network
failures & appearing as a single, highly available service.
15. 4store
4store is a
database storage and query engine that holds RDF data. It is written in
ANSI C99, designed to run on UNIX-like systems & offers a high
performance, scalable & stable platform.
16. MariaDB
MariaDB is a
backward compatible, drop-in replacement branch of the MySQL? Database
Server. It includes all major open source storage engines + the Maria
storage engine.
17. Drizzle
It is a fork of MySQL that focuses on being a reliable database optimized for Cloud and Net applications.
18. HyperSQL
It is a SQL
relational database engine written in Java. HyperSQL offers a small
& fast database engine which has in-memory and disk-based tables,
supports embedded/server modes. Also, it has tools such as a command
line SQL tool & GUI query apps.
19. MonetDB
MonetDB is a
database system for high-performance applications in data mining, OLAP,
GIS, XML Query, text & multimedia retrieval.
20. Persevere
It is an object
storage engine and application server (running on Java/Rhino) that
provides storage of dynamic JSON data for rapidly develop data-driven
JavaScript-based rich internet applications.
21. eXist-db
eXist-db is
built using XML technology. It stores XML data according to the XML data
model & features efficient, index-based XQuery processing.
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