Apache Hive vs. MariaDB Platform

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Hive
Score 8.0 out of 10
N/A
Apache Hive is database/data warehouse software that supports data querying and analysis of large datasets stored in the Hadoop distributed file system (HDFS) and other compatible systems, and is distributed under an open source license.N/A
MariaDB Platform
Score 9.2 out of 10
N/A
MariaDB is an open-source relational database made by the original developers of MySQL, supported by the MariaDB Foundation and a community of developers. The community states recent additional capabilities as including clustering with Galera Cluster 4, compatibility with Oracle Database, and Temporal Data Tables, allowing one to query the data as it stood at any point in the past.N/A
Pricing
Apache HiveMariaDB Platform
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache HiveMariaDB Platform
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeOptional
Additional Details
More Pricing Information
Community Pulse
Apache HiveMariaDB Platform
Considered Both Products
Apache Hive
Chose Apache Hive
To query a huge, distributed dataset, Apache Hive was built by Facebook. Unlike Apache Hive, Apache Spark is an in-memory computation engine, which is why it is significantly quicker than Apache Hive at querying large amounts of data. In contrast to Apache HBase, Apache Hive is …
Chose Apache Hive
Apache hive gave more flexible than MS SQL server. ElasticSearch was little complex. GoogleBigQuery cost more.
Chose Apache Hive
Community support and ease of use -not deployment.

It enables querying and analyzing large amounts of data stored in HDFS, on the petabyte scale. It has a query language called HQL that transforms SQL queries into MapReduce jobs that run on Hadoop, and it is wonderful for the …
Chose Apache Hive
Apache Spark is similar in the sense that it too can be used to query and process large amounts of data through its Dataframe interface. Hive is better for short-term querying while Spark is better for persistent and long-term analysis. Another product is Impala. For our …
Chose Apache Hive
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, …
Chose Apache Hive
Apache Hadoop is built on top of the Hadoop File system so it gives its best when integrated with Hadoop. Data analysis and query optimization become very easy when used with Hadoop to perform Extract transform load operations. As Hadoop is a big data system and handles large …
Chose Apache Hive
We have used the system to migrate data either for new versions or because we will use another operating program, the software helps us to synchronize programs between different operating systems, a history of information can be kept constant, it can be sent to third parties …
Chose Apache Hive
Queries are easy to write and interface is similar to SQL so learning overhead is reduced. Multi user and data type support is provided. Can be easily scaled for very large amount of analytics. It is very flexible in terms of using file formats.
Chose Apache Hive
Snowflake, Splunk Cloud, Talend Open Studio, Azure Data Factory and Apache Spark
Chose Apache Hive
Due to effective queries resolved time and the performance and user-friendly framework compared to other products.
Chose Apache Hive
Apache Hive is a query language developed by Facebook to query over a large distributed dataset. Apache is a query engine that runs on top of HDFS, so it utilizes the resources of HDFS Hadoop setup, while Apache Spark is an in memory compute engine, and that's why [it is] much …
Chose Apache Hive
Besides Hive, I have used Google BigQuery, which is costly but have very high computation speed.
Amazon Redshift is the another product, I used in my recent organisation.
Both Redshift and BigQuery are managed solution whereas Hive needs to be managed
Chose Apache Hive
Hive and Spark have the same parent company hence they share a lot of common features. Hive follows SQL syntax while Spark has support for RDD, DataFrame API. DataFrame API supports both SQL syntax and has custom functions to perform the same functionality. Spark is faster and …
Chose Apache Hive
Apache Hive decouples the query layer from the storage layer, it is more flexible and expandable.
Chose Apache Hive
One of the major advantages of using Presto or the main reason why people use Presto (Teradata) is due to that fact it can support multiple data sources - which is lacking as in the case of Apache Hive. But still, most people who come from a Structured data-based background …
Chose Apache Hive
Easy to understand, well supported by the community, good documentation. However, it is possible that SAP Business Warehouse could be a good fit, too, even maybe better. I did not have the chance to try it though. We selected Apache Hive because it was far less expensive and …
Chose Apache Hive
I considered Hive because it is the best suited option when it comes to larger data access. Besides, learning HiveQL is comparatively easy.
Chose Apache Hive
I have used Storm for real-time processing, but that only addresses a few data points. But for a larger access to data, Hive is well suited.
Chose Apache Hive
[We selected Apache Hive because] It's from apache and opensource. So it's free.
Chose Apache Hive
  • Faster response time and also can handle complex analytical queries
  • Can able to write custom function using python and hive
  • Able to connect using hadoop components and also using R
Chose Apache Hive

For storing bulk amount of data in a tabular manner, and where there's no need need of primary key, or just in case, if redundant data is received, it will not cause a problem. For small amounts of data, it does run MR, so beware. If your intention is to use it as a …

Chose Apache Hive
I wasn't part of the evaluation process for Apache Hive. This was already implemented when I joined the company. I have worked with other big data plaftforms and I personally thinks most of them are quite comporable to one another. It really depends on what the company is going …
Chose Apache Hive
Hive is SQL compliant which makes it easy for the data folks compared to Pig
Chose Apache Hive
Apache Pig is probably the most direct technology to compare to Hive and has several different use cases to Hive. If you want to simplify processing tasks that run using MapReduce then Apache Pig may be a better tool for the job. However if you are going to be running many …
MariaDB Platform
Chose MariaDB Platform
MariaDB is perhaps the best open source database server available, combining a wide range of supported platforms, MySQL compatibility, a low footprint, and reasonably high performance. If you have cost constraints, or limited server resources, I recommend MariaDB, particularly …
Chose MariaDB Platform
MS SQL Server is like a BlackBox in many cases. Honestly we did not need advanced functionality that SQL server offers, just a plain DBMS. MariaDB is easier to manage, cross operating system, "lighter" with better performances than SQL server. We went with MariaDB Platform even …
Chose MariaDB Platform
It did not always compete against these technologies. Most of the time, it was complementing these databases for certain use cases to help provide a much more complete database. This makes more users want to use it to explore new solutions that help users. This is our target …
Chose MariaDB Platform
I've only used MariaDB Platform.
Chose MariaDB Platform
MariaDB gives a low-cost option for DB engines like Oracle with plenty of features and flexibility while having better ease of use than Postgresql.
Chose MariaDB Platform
We tried Percona also, but we sometimes having trouble with it and on some cases it having lesser performance than MariaDB.
MySQL is the the facto standard, we use this only in scenario that it cannot be replaced by MariaDB.
MSSQL is used only if the client ask for Windows …
Chose MariaDB Platform
We were already wanting to migrate away from Cassandra for reasons of stability, cost (more servers were needed), and our data storage model. We evaluated PostgreSQL but passed on it due to being more familiar with MariaDB. Also we needed something that could do multi-region …
Chose MariaDB Platform
MariaDB is very similar to MySQL, but MariaDB has more alternative database engines and ideas for the future where MySQL is offers the stable and more mature version (if not stale).

Chose MariaDB Platform
(With and without RAC) My company migrated from Oracle to MariaDB. While MariaDB has some limitations (if you are used to Oracle) it has been much easier and cheaper (in several ways) to operate and has more than met my company's needs.
Chose MariaDB Platform
MariaDB is the clear winner compared to any other database I've used. Reliable, scale-able, affordable--you name the consideration and MariaDB is the winner.
Chose MariaDB Platform
MariaDB is much easier to set up and maintain compared to PostgreSQL makes it much faster to launch our application and relatively easier to upgrade its version so we can make sure the installed version is up to date with the latest patch, which is especially important if we …
Chose MariaDB Platform
MySQL is still a great solution, but MariaDB offers a more extensive set of free features than are available for MySQL. We also feel more confident that MariaDB will remain free to use over time. End users haven't noticed much of a difference, but from a development cost …
Chose MariaDB Platform
MariaDB stacks up the the competition just fine. Due to is ture open source nature we do not have to worry about licencing and spending money on nothing. Moreover, MariaDB does everything that we need to get done. We can run data that is a million rows or many smaller projects …
Chose MariaDB Platform
MariaDB provided the best fit for our business in upgrading legacy systems which were originally designed to use MySQL as a backend. By using MariaDB, no changes to the overall systems needed to be altered, reducing the time needed to upgrade everything. Other solutions …
Chose MariaDB Platform
We had previously used MySQL, but our database has grown very large. MariaDB offers faster queries.
Chose MariaDB Platform
Thanks to MySQL compatibility, everything you've learned while using it can be utilized when using MariaDB. Therefore it's a better choice than MongoDB and MSSQL if you're looking to switch away from MySQL. MariaDB is also a very mature and stable product, unlike MongoDB that …
Chose MariaDB Platform
MariaDB is cheaper than Oracle Database and MSSQL server. MySQL owned by Oracle. So MariaDB has too many forks, but enough people in the community. PostgreSQL has a larger community and better administration. However, it s not like MariaDB w/ Galera. MariaDB is not good for …
Chose MariaDB Platform
We know others DB alternatives like MySQL, Microsoft SQLServer, PostgreSQL. We selected MariaDB because it offer advanced features like active-active cluster, with no costs and easy to learn. With MariaDB was easy to migrate ours applications that use MySQL, with no …
Chose MariaDB Platform
We selected MariaDB over MySQL because of their true open source model and performance optimizations. It was also helpful that it is a drop-in replacement for MySQL so there was no need to update our various software drivers.
Chose MariaDB Platform
MariaDB costs much less than SQL Server to acquire and maintain. In comparison to Cassandra, it gives us operational use and helps in Agile development.
Best Alternatives
Apache HiveMariaDB Platform
Small Businesses
Google BigQuery
Google BigQuery
Score 8.7 out of 10
InfluxDB
InfluxDB
Score 9.0 out of 10
Medium-sized Companies
Cloudera Enterprise Data Hub
Cloudera Enterprise Data Hub
Score 9.0 out of 10
SQLite
SQLite
Score 8.0 out of 10
Enterprises
Oracle Exadata
Oracle Exadata
Score 9.8 out of 10
SQLite
SQLite
Score 8.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache HiveMariaDB Platform
Likelihood to Recommend
8.0
(0 ratings)
10.0
(0 ratings)
Likelihood to Renew
10.0
(0 ratings)
-
(0 ratings)
Usability
8.5
(0 ratings)
10.0
(0 ratings)
Support Rating
7.0
(0 ratings)
8.7
(0 ratings)
User Testimonials
Apache HiveMariaDB Platform
Likelihood to Recommend
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.
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Our installation scenario is a MariaDB cluster composed of 3 nodes to achieve high availability in the service and in this way the application that accesses the backend (MariaDB) is always working and is not down at any time.
To achieve high performance of the application when accessing the database, a MariaDB MaxScale has been mounted that acts as a proxy for queries to the database.
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Pros
  • 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.
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  • MariaDB does well with PHP or Python (django) in a web environment. Developers are able to work quickly.
  • MariaDB is extremely well documented and has a gigantic support community. If you need ask a question on how to do things you can go to many placces online and find answers quickly.
  • MariaDB is fast! Queries with tens of thousands of rows are quick.
  • MariaDB is highly compatible with Oracle's MySQL. Basically the same thing but more open and with a brighter future.
  • With MariaDB it is so easy to import and export data, and backups are a cinch. This saves me so much time as compared to other RDBMS.
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Cons
  • 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.
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  • Driver Support - Some third party applications use database drivers that cause unexplained slowness with MariaDB. This can be worked around by using the MySQL drivers, but it's not clear what causes the problem in the first place.
  • Support - While online communities are helpful in diagnosing problems, there isn't as much professional documentation/support available for MariaDB as some of the other major database options.
  • Data Visualization - It would be helpful if there were more built in options for analyzing statistics and generating reports.
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Likelihood to Renew
Since I do not know the second data warehouse solution that integrate with HDFS as well as Hive.
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No answers on this topic
Usability
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.
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MariaDB is very usable and stable to be used in production settings as an alternative to MySQL. The shortcomings of SQL are present but well understood in the community, and if the decision were to be made again, I would choose MariaDB over MySQL on future projects.
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Support Rating
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.
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Yes, I would recommend MariaDB Platform support because they answer very fast and with detailed information. They also help you with the design of the storage infrastructure, not only with the maintenance problems. On the other hand, this service is a bit expensive.
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Alternatives Considered
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.
Read full review
It did not always compete against these technologies. Most of the time, it was complementing these databases for certain use cases to help provide a much more complete database. This makes more users want to use it to explore new solutions that help users. This is our target and how [we] work with MariaDb.
Read full review
Return on Investment
  • 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
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  • MariaDB has saved us enormously on licensing compared to our previous DB software vendor.
  • In service, it has enabled us (speaking as the internal DB team here) to provide better service to the other teams in the company as well as our customers, with less staff.
  • The level of hardware required for adequate performance, in our environment, has been much lower. Those savings have been substantial, above and beyond savings on licensing and DBA staffing levels.
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