Only a few years ago, database work was among the most boring of tasks in IT -- in a good way. Data went into one of the major SQL databases and it came out later, all in one piece, exactly as it went in. The database creators had succeeded in delivering rock-solid performance, and everyone started taking it for granted.
Then the nature of what we wanted to store changed. Databases had to move beyond bank accounts and airline tickets because everyone had begun sharing data on social networks. Suddenly there was much more data to store, and most of this new data didn’t fit into the old tables. The work of database admins and creators transformed, and what has emerged is a wide array of intriguing solutions that help to make databases among the more intriguing technologies today.
Cassandra, MongoDB, CouchDB, Riak, Neo4j -- the innovations of the past several years are by now well-established at many organizations. But a new generation is fast rising. Here we provide an overview of 11 cutting-edge databases tuned to store more data in more flexible formats on more machines in a way that can be queried in a variety of ways.
The database world has never been as varied and interesting as it is right now.
When a few refugees from Twitter wanted to build something new with the experience they gained processing billions of tweets, they decided that a distributed database was the right challenge. Enter FaunaDB. In goes the JSON, and out come answers from a distributed collection of nodes. FaunaDB’s query language offers the ability to ask complex questions that join together data from different nodes while searching through social networks and other graph structures in your databases.
If you’re simply interested in experimenting or you don’t want the hassle of rolling your own, FaunaDB comes in a cloud database-as-a-service version. When and if you want to take more control, you can install the enterprise version on your own iron.
You wouldn’t be the first architect to throw up your hands and say, "If only we could mix the flexibility of document-style databases with the special power of graph databases and still get the flexibility of tabular data. Then we would have it made."
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