bitdigg（该选择哪个开源数据库）

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• 该选择哪个开源数据库
• 如何用bitdigg搜索vr资源

该选择哪个开源数据库

21 个最好的免费开源数据库：
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 Facebook, Digg, Twitter, 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.

如何用bitdigg搜索vr资源

• 现在已经搜索不到了，很多已经被封，我这还保存了一点

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  邀  h520   v   垃   C   〇  m

  这个异常处理器监视try后面的程序块。

  catch的括号有一个参数，代表所要捕捉的异常的类型。

  catch会捕捉相应的类型及其衍生类。try后面的程序块包含了针对该异常类型所要进行的操作。

  try所监视的程序块可能抛出不止一种类型的异常，所以一个异常处理器可以有多个catch模块。finally后面的程序块是无论是否发生异常，都要执行的程序。