Apache Hive vs. SQLite

Apache Hive shines for ad-hoc analysis and plugging into BI tools. Its SQL-like syntax allows for ease of use not for only for engineers but also for data analysts. Through our experience, there are probably more desirable tools to use if you are planning on integrating Hive into your processing pipeline.

Incentivized

The portability and ease of use has us doing local development, and then shipping the database to production for implementation. This compact deliverable object is great. Until multiple developers need to access it at a time. It is a caveat, but we create a database per integration as it is easier to manage. Using a SQLite database to manage more than one integration or task is not something we would recommend.

Incentivized

• Hive syntax is almost like SQL, so for someone already familiar with SQL it takes almost no effort to pick up Hive.
• To be able to run map reduce jobs using json parsing and generate dynamic partitions in parquet file format.
• Simplifies your experience with Hadoop especially for non-technical/coding partners.

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

• Use Hive for analytical work loads. Write once and read many scenarios. Do not prefer updates and deletes.
• Behind scenes Hive creates map reduce jobs. Hive performance is slow compared to Apache Spark.
• Map reduce writes the intermediate outputs to dial whereas Spark operates in in-memory and uses DAG.

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

Since I do not know the second data warehouse solution that integrate with HDFS as well as Hive.

Hive is a very good big data analysis and ad-hoc query platform, which supports scaling also. The BI processes can be easily integrated with Hadoop via the Hive. It can deal with a much larger data set that traditional RDBMS can not. It is a "must-have" component of the big data domain.

Incentivized

I have had a wonderful experience with SQLite because in my every project I use SQLite in the development phase because it's really fast, doesn't crash and very easy to maintain as well. It saves a lot on physical memory and dedicated server usage. It has all the basic functionality you would need to get the job done and that too at no cost at all. What more could you ask for !!!

Incentivized

Apache Hive is a FOSS project and its open source. We need not definitely comment on anything about the support of open source and its developer community. But, it has got tremendous developer support, awesome documentation. I would justify the fact that much support can be gathered from the community backup.

Incentivized

I haven't needed support yet.

Incentivized

We have used a simple but necessary function such as merging certain data tables, which although they may be from different areas, complement each other or are necessary, you can use metadata if what you need is to validate the origin of your information and what impact it has, is also feasible.

Incentivized

SQLite has CRUD queries and manipulates external files. Cross-platform support includes iOS, Android, Mac OS X, and Windows. Compared to other databases, it is fast and straightforward to implement. Even if an application crashes, there is no effect on the database or the data it contains. The user interface is best for input and output. It's best for developing skills and project deliverables.

Incentivized

• Good ROI for being able to access data easily across the network, we have large amounts of data and this is a good system to access it
• Good ROI for being easy to learn how to use for new employees, not much time spent which saves costs
• Good ROI for being able to integrate with Spark and other applications, hence data can be analyzed through programs

Incentivized

• 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