Apache Derby vs. Neo4j vs. SQLite

If you need a SQL-capable database-like solution that is file-based and embeddable in your existing Java Virtual Machine processes, Apache Derby is an open-source, zero cost, robust and performant option. You can use it to store structured relational data but in small files that can be deployed right alongside with your solution, such as storing a set of relational master data or configuration settings inside your binary package that is deployed/installed on servers or client machines.

Incentivized

Neo4J is great for creating network graphs or illustrating how things are related. It is also good for finding individuals or things that have greater influence than others in a system. It is not appropriate if you have standard data sets that can be analyzed using conventional methods or visualized using Tableau, for example.

Incentivized

SQLite is a lightweight and efficient database management system. With SQLite, performance increases as memory are added. It's reliable and well-tested before release. SQLite handles memory allocation and I/O errors gracefully. SQLite provides bug lists and code-change chronologies. All bugs are disclosed, and it's compatible with iOS, Android, MAC, and Windows. SQLite is open-source, allowing developers to tailor it to their specific needs.

Incentivized

• Apache Derby is SMALL. Compared to an enterprise scale system such as MSSQL, it's footprint is very tiny, and it works well as a local database.
• The SPEED. I have found that Apache Derby is very fast, given the environment I was developing in.
• Based in JAVA (I know that's an obvious thing to say), but Java allows you to write some elegant Object Oriented structures, thus allowing for fast, Agile test cases against the database.
• Derby is EASY to implement and can be accessed from a console with little difficulty. Making it appropriate for everything from small embedded systems (i.e. just a bash shell and a little bit of supporting libraries) to massive workstations.

Incentivized

• Mature Query language, I found Cypher QL to be mature in handling all sorts of problems we throw at it. Its expressive enough to be intuitive while providing rich features for various scenarios.
• Native support for REST API, that makes interacting with Neo4J intuitive and easy.
• Support for Procedures in Java, procedures are custom code that could be added to the Neo4J to write custom querying of data. The best part about the procedures is it could be invoked using the REST API. This allows us to overcome any shortcomings from their Cypher query language.
• Nice UI and interface for executing the Query and visualizing the response.
• UI access controlled by User credentials allows for neat access controls.
• Awesome free community edition for small-scale projects.

Incentivized

• Our products are using SQLite in embedded Linux and in Windows software.
• It is truly a stable cross-platform database.
• The fact that it is a zero-configuration database engine, it is particularly a nice advantage when you work in the embedded world.
• Being a single database file, it provides ease for those who need to quickly transfer data to someone else, or quickly browse data.

Incentivized

• It may not scale as well as some more mature database products.
• Used it primarily from the command line with openjpa and jdbc, and from third-party clients such as Squirrel.
• May benefit by providing more sophisticated tools to optimize query performance.

Incentivized

• One of the hardest challenges that Neo4j had to solve was the horizontal scaling problem. I am not updated on recent developments, but at the time of my use, I couldn't find a viable solution.
• Neo4j does not play with other open source APIs like Blueprint. You have to use the native Neo4j API.
• There wasn't a visual tool to see your data. Of course, third party tools are always available, but I would have loved something which came with the Neo4j bundle. I love that Docker comes bundled with Kitematic, so it's not wrong to hope that Neo4j could also ship with some default visualization software.

Incentivized

• Although it is excellent at what it does, you should be really careful and plan accordingly if you know that your database is going to scale at a huge level because it is not suitable of databases which are of Enterprise level and demands top-notch security and protection.
• If your project involves multiple people working on the same database simultaneously, then that becomes a big problem, because it only allows single write at one time. You really need to be forward thinking in a manner to predict if this database will cater to all the needs of your project.
• The most common difficulty with this is the lack of some of the basic functionality which is present in the other premier databases like Joints, Stored Procedure calls, Security and permission grants. If you do require all those things then you are better off not using this software.
• Lastly, if you are using this in an Andriod App development cycle then also your options are limited because it does not integrate with PostgreSQL and MYSQL.

Incentivized

Learning cypher was super easy coming from a SQL background. Furthermore, the docs Neo4j provides on their website make it really easy to pull up a reference, guide or a quick example. The mac app they provide is also really well designed with good visualisation tools, with the ability to easily use colour, line thickness etc to help navigate your data.

Incentivized

I have given this rating cause its irreplaceable in some of the areas like no more installation need except from a single library. I find dialect is simple in use cases. its suitable for any professionals with various skill levels. its easily connect with various os and devices. very less maintenance or administration required.

Incentivized

I haven't needed support yet.

Incentivized

SQLite is another open-source zero-cost file-based SQL-capable database solution and is a good alternative to Apache Derby, especially for non-Java-based solutions. We chose Apache Derby as it is Java-based, and so is the solution we embedded it in. However, SQLite has a similar feature set and is widely used in the industry to serve the same purposes for native solutions such as C or C++-based products.

Incentivized

Neo4j is a graph store and has different use cases compared to another NoSQL Document store like MongoDB. MongoDB is a bad choice when joins are common as existing operators for joining two documents (similar to tables in a relational store) as Mongo 3.5 use SQL like join algorithms which are expensive. MongoDB is a great choice when distributed schemaless rich document structures are important requirements. Cross document transaction support is not native to MongoDB yet, whereas Neo4J is ACID complaint with all its operations.

Incentivized

We looked at other traditional RDBMS products, but found them to be cumbersome to deploy. They take up more space, and consume more computing resources than SQLite does. While the performance or direct integration to our primary applications may have been better or easier if we had gone with a traditional RDBMS, the performance of SQLite has been more than acceptable. The performance and speed to deploy made SQLite a much more attractive option for us than a traditional RDBMS.

Incentivized

• Being Open source, the resources spent on the purchase of the product are ZERO.
• Contrary to popular belief, open source software CAN provide support, provided that the developers/contributors are willing to answer your emails.
• Overall, the ROI was positive: being able to experiment with an open source technology that could perform on par with the corporate products was promising, and gave us much information about how to proceed in the future.

Incentivized

• Positive: Less complex queries on graph structures, than in relational databases.
• Negative: maintenance is a huge deal, things doesn't work and break, requiring lengthy restore operations.

• No licensing fees has a net increase on ROI
• The active community has kept support costs low, further increasing ROI
• The wide range of supported platforms and high level of compatibility has increased ROI by reducing time spent porting the database model to any platform specific solutions.

Incentivized