Apache Hive vs. ParAccel

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Hive
Score 8.2 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
ParAccel
Score 8.8 out of 10
N/A
ParAccel was a data warehouse appliance (DWA) option, offered by Actian since the April 2013 acquisition of ParAccel as Actian Matrix, that has since been discontinued.N/A
Pricing
Apache HiveParAccel
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache HiveParAccel
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Best Alternatives
Apache HiveParAccel
Small Businesses
Google BigQuery
Google BigQuery
Score 8.6 out of 10
Google BigQuery
Google BigQuery
Score 8.6 out of 10
Medium-sized Companies
Cloudera Enterprise Data Hub
Cloudera Enterprise Data Hub
Score 9.0 out of 10
Cloudera Enterprise Data Hub
Cloudera Enterprise Data Hub
Score 9.0 out of 10
Enterprises
Oracle Exadata
Oracle Exadata
Score 8.0 out of 10
Oracle Exadata
Oracle Exadata
Score 8.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache HiveParAccel
Likelihood to Recommend
8.0
(35 ratings)
8.8
(3 ratings)
Likelihood to Renew
10.0
(1 ratings)
6.0
(1 ratings)
Usability
8.5
(7 ratings)
6.0
(1 ratings)
Support Rating
7.0
(6 ratings)
8.0
(1 ratings)
Implementation Rating
-
(0 ratings)
6.0
(1 ratings)
User Testimonials
Apache HiveParAccel
Likelihood to Recommend
Apache
Software work execution is on a large scale, it is good to use for new projects or organizational changes, data lineage mapping has always been dubious but this one has had good results. You can store and synchronize data from different departments, the storage process can be manual but it is best automated.
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Discontinued Products
Actian matrix is not good for small data sets. If you have a limited data pool, or do not plan on having multiple users/clients accessing a data source, stick with a more traditional relational database model - Access for the truly small user base, or a DB2 or Oracle back end if your going to have multiple users, and moderate sized data. Actian is for LARGE data sets (Big Data, in the industry parlance). Millions of rows of data from multiple sources with various down stream systems accessing the database. It is for data analytics of large data groups and intense data mining.
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Pros
Apache
  • Apache Hive allows use to write expressive solutions to complex problems thanks to its SQL-like syntax.
  • Relatively easy to set up and start using.
  • Very little ramp-up to start using the actual product, documentation is very thorough, there is an active community, and the code base is constantly being improved.
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Discontinued Products
  • Super fast. Aggregate query such as SUM(), Count() returns result within seconds from a table with more than billion records.
  • Excellent data compression.
  • Easy maintenance. We managed this database without having a full time DBA.
  • Support ANSI SQL and ODBC/JDBC. It's easy to connect to this database from other systems.
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Cons
Apache
  • Some queries, particularly complex joins, are still quite slow and can take hours
  • Previous jobs and queries are not stored sometimes
  • Switching to Impala can sometimes be time-consuming (i.e. the system hangs, or is slow to respond).
  • Sometimes, directories and tables don't load properly which causes confusion
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Discontinued Products
  • Some of the bugs were annoying and QA definitely needs improvement
  • Connectivity to Informatica and ETL providers
  • Workload management could be better like when you compare with Teradata
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Likelihood to Renew
Apache
Since I do not know the second data warehouse solution that integrate with HDFS as well as Hive.
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Discontinued Products
No answers on this topic
Usability
Apache
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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Discontinued Products
I wish to give higher rating for the speed and efficiency in handling the queries, but only 6 because of consistent bugs we encounter
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Support Rating
Apache
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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Discontinued Products
  • Faster initial response
  • Trained professionals
  • Very helpful in resolving issues
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Implementation Rating
Apache
No answers on this topic
Discontinued Products
Leader failover setup is the toughest and lack of proper documentation is making things tough.
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Alternatives Considered
Apache
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
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Discontinued Products
Actian Matrix is our first big data analytics storage platform, and as I was not involved in the POC process to compare it to other products out on the market, unfortunately I cannot say if it is better than other Big Data storage options. I can say that it out performs products such as Oracle or UDB in regards to the volume of data it can easily index and handle.
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Return on Investment
Apache
  • Apache hive is secured and scalable solution that helps in increasing the overall organization productivity.
  • Apache hive can handle and process large amount of data in a sufficient time manner.
  • It simplifies writing SQL queries, hence helping the organization as most companies use SQL for all query jobs.
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Discontinued Products
  • ROI is great, less spending on full time DBA and that money could be use to add additional node.
  • Negative - Not many developers are well aware of this tool, it takes some time to learn.
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