What does “Scale” even mean in the context of databases? When talking about scaling, people have jumped to the vendor-induced conclusion that SQL doesn’t scale, while NoSQL scales. In this article, the author takes a look at database scalability by comparing Oracle benchmarks to MongoDB.
A new feature of MarkLogic 7′s search API is range index scoring – affecting relevancy based on a value within a document. In this article, the author details a couple of use cases: One involving ratings, and one involving distance from the center point of a geospatial query.
In a couple of Neo4j talks, the author has been asked how long it takes to get used to modeling data in graphs and whether he felt it's simpler than alternative approaches. His experience closely mirrors what he believes is a fairly common curve when learning technologies that change the way you think.
The author was in the middle of upgrading a little test project to a newer version of Spring Data Neo4j and Neo4j itself when he came across a few little points that others might find useful. Here are a couple "gotchas" he encountered.
One graph database vendor decided to divide the graph database space into non-native (i.e. square) and native (i.e. diamond) graph databases. Obviously, non-native is boring, or slow, or simply bad, and native is exciting, or fast, or simply good. Problem is: There is no such thing as a native graph database.
There isn’t too much information about using MongoDB with SSL connections out there. If you are using MongoDB on a public network, all the data you transmit from the database to your application is completely unencrypted. Luckily however, MongoDB offers the option to be compiled with SSL support.
One of the additional features that Neo4j enterprise provides is access to various JMX properties which describe various aspects of the database.
In MongoDB query analysis, you can use the built-in queries (after all, the profiling is saved in a MongoDB collection). However, Dex, a tool from MongoLab, can help you shorten the time to index...
Make sure you didn't miss anything with this list of the Best of the Week in the NoSQL Zone. This week's best include a discussion of the relationship between relational databases and their predecessors, thoughts about compression and storage in LevelDB and LMDB, and an argument that SQL is the new NoNoSQL.
In the author's previous post, he demonstrated how fast you can insert 50 million time-event entries with MongoDB. In this article, you will learn how to make use of all that data to fuel aggregation tests.
This recent post details a database migration from MongoDB to Cassandra. It's a detailed account, starting with the background of what led to the decision, various attempts at solving their problems, and finally how they went about migrating to Cassandra, including code and data to document their improvements.
When the author started running some years ago, he bought a Garmin Forerunner 405, a device that tracks GPS coordinates while you're running. In this article, you will learn how to store, query, and visualize such data using a Neo4j Spatial datastore and Gephi.
Using disk snapshots to perform MariaDB backups has become more and more common, but this seems to have been limited to Linux and Cloud environments. There has been a notion that Snapshots cannot be done on native Windows, the way we can do snapshots using LVM on Linux, for example.
Recently, Datablend open-sourced two new Tinkerpop Blueprints implementations: blueprints-mongodb-graph and blueprints-datomic-graph. Tinkerpop is an open source project that provides an entire stack of technologies within the Graph Database space.
The author has been playing around with Neo4j on a Windows VM recently, and he wanted to launch neo4j-shell to run a few queries. In this article, you'll learn how to deal with the problems he faced between Neo4j Shell, Neo4j Desktop, and the command prompt.
Recently, Dan wrote a great piece on testing network failures with NuoDB's support for geo-distribution. If you haven't read it, then go do that right now. It's cool, and it illustrates pretty clearly how you can tune the rules for durability based on awareness of regions.
Some websites are made to inspire debate, and this is one: "NoSQL vs. SQL: SQL is the new NoNoSQL." It contains a side-by-side comparison of SQL and NoSQL in general, answering questions such as "is it based upon a rock-solid theory," "will it still be there in 10 years," "can it scale up," and many more.
There is always the risk that communication between database nodes is affected by either a break in the network link or a partition of the network space. To handle such network problems, NuoDB has a failure detection system. In this article, you'll learn the basics of this system and how to enable it.
This article takes an interesting look at MongoDB by highlighting its limitations, not to criticize or demonize MongoDB, but to clarify weaknesses in order to prevent lack of user understanding from misrepresenting it. In other words, you can't blame a screwdriver for not being a hammer.
The author has been trying to get the hang of Cypher’s MERGE function, and started out by writing a small file to import some people with random properties using the java-faker library. In this article, you'll learn more about the MERGE function.
The new MarkLogic Node.js and widget API has been released. In this article, you'll find an overview of new features and changes, as well as where to find the code, instructions, and tutorials to get started.
Make sure you didn't miss anything with this list of the Best of the Week in the NoSQL Zone. This week's best include a discussion of the need (or lack of need) of eventually consistent data, a critique of last year's wave of MongoDB criticisms, an alternative NoSQL solution called ArangoDB, and more.
One of the things that the author liked in LevelDB is that it pretty much had compression built in from day one. The entire format is built to save space just about wherever it can. LMDB, in contrast, went quite the opposite way.
Much of the NoSQL movement feels like a rebellion against the “old timey” feeling relational databases. The author thought it would be fascinating to dig into the value of relational databases. In short, relational databases were the noSomething, and he aimed to find out what that something was.
In NuoDB 2.0.1, a region is a property that represents a geographic location for the database. Such locations might include a data center in a major city, country, or building location. This article describes how to configure a NuoDB database to include geographical regions and region-level commits.