Apache HBase vs. Apache Parquet

Apache HBase

Apache HBase

32 Reviews and Ratings

Apache Parquet

Apache Parquet

0 Reviews and Ratings

Overview
Product	Rating	Most Used By	Product Summary	Starting Price
HBase	Score 7.3 out of 10	N/A	The Apache HBase project's goal is the hosting of very large tables -- billions of rows X millions of columns -- atop clusters of commodity hardware. Apache HBase is an open-source, distributed, versioned, non-relational database modeled after Google's Bigtable.	N/A
Apache Parquet	Score 0.0 out of 10	N/A	Apache Parquet is an open source and free, column-oriented data file format designed for efficient data storage and retrieval. It provides data compression and encoding schemes with enhanced performance to handle complex data in bulk. Parquet is available in multiple languages including Java, C++, Python, etc.	N/A

Pricing

Apache HBase

Apache Parquet

Editions & Modules

No answers on this topic

No answers on this topic

Offerings

Pricing Offerings
HBase	Apache Parquet
Free Trial
No	No
Free/Freemium Version
No	Yes
Premium Consulting/Integration Services
No	No

Entry-level Setup Fee

No setup fee

No setup fee

Additional Details

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More Pricing Information

Community Pulse
	Apache HBase	Apache Parquet
Considered Both Products	HBase RAVI MISHRA Data Engineer Chose HBase HBase is more secure. Easily scalable. HBase is for wide-column store while MongoDB is for document store. Triggers available in HBase while in Mongodb triggers are not available. Incentivized Helpful? Bharadwaj (Brad) Chivukula Director Of Engineering/Head of Reliability Engineering Chose HBase Hbase is more robust and scalable than other DBs around Incentivized Helpful? Anson Abraham Data Lord Chose HBase Cassandra os great for writes. But with large datasets, depending, not as great as HBASE. Cassandra does support parquet now. HBase still performance issues. Cassandra has use cases of being used as time series. HBase, it fails miserably. GeoSpatial data, Hbase does work … Incentivized Helpful? Vinaybabu Raghunandha Naidu Software Engineer - Big Data Platform Chose HBase Compared NoSQL databases with traditional databases for faster retrieval and consistency. As MongoDB is a NoSQL supports dynamic fields, however, query performance is bad for aggregations and added maintenance. When compared with MySql and Teradata, it could not scale up as … Incentivized Helpful? Timothy Spann Senior Solutions Engineer Chose HBase HBase is what you should use if you want a production ready scalable, JSON friendly, key-value, NoSQL, enterprise storage option. It excels over MongoDB due to integration with the extensive Hadoop stack and all the tools, frameworks and benefits there. HBase has superior … Incentivized Helpful? Verified User Anonymous Chose HBase Typically, Cassandra is faster on reads and HBase is faster on writes. You use Cassandra when you want to use a website, HBase is just an overall good general use database engine. Cassandra has its own storage engine and HBase uses HDFS and all its benefits. MongoDB is … Incentivized Helpful? Zack Riesland Data Engineer / Software Engineer (Big Data - Cloud) Chose HBase Hbase is less robust but faster. Incentivized Helpful? Rekha Joshi Staff Software Engineer Chose HBase These days I use Apache Cassandra more for even more scalability, good performance under different kind of workloads, and for providing highly available systems. Apache Cassandra also has connectors for Hadoop, Spark, and Solr. Incentivized Helpful?	Apache Parquet No answer on this topic

Features

Apache HBase

Apache Parquet

NoSQL Databases

Comparison of NoSQL Databases features of Product A and Product B
	Apache HBase 7.7 Ratings 14% below category average	Apache Parquet - Ratings
Performance	7.10 Ratings	00 Ratings
Availability	7.80 Ratings	00 Ratings
Concurrency	7.00 Ratings	00 Ratings
Security	7.80 Ratings	00 Ratings
Scalability	8.60 Ratings	00 Ratings
Data model flexibility	7.10 Ratings	00 Ratings
Deployment model flexibility	8.20 Ratings	00 Ratings

Best Alternatives
	Apache HBase	Apache Parquet
Small Businesses	IBM Cloudant Score 7.4 out of 10	IBM Cloudant Score 7.4 out of 10
Medium-sized Companies	IBM Cloudant Score 7.4 out of 10	IBM Cloudant Score 7.4 out of 10
Enterprises	IBM Cloudant Score 7.4 out of 10	IBM Cloudant Score 7.4 out of 10
All Alternatives	View all alternatives	View all alternatives

User Ratings
	Apache HBase	Apache Parquet
Likelihood to Recommend	7.7 (0 ratings)	- (0 ratings)
Likelihood to Renew	7.9 (0 ratings)	- (0 ratings)

User Testimonials
	Apache HBase	Apache Parquet
Likelihood to Recommend	HBase is well suited for streaming ingest, fast lookups, massive datasets, data warehouse lookup tables, RDBMS replacement, MongoDB replacement, key-value store, data scans, logs, JSON storage and some binary storage. My preferred use case is for storing data points like time series or data produced by sensors. I often use HBase when I need data available immediately and I am not looking for transactions. This is a great store for really wide tables with tons of columns. It is also great if you are not sure what type of data you are going to have. It really excels at sparse data. Incentivized Timothy Spann Senior Solutions Engineer Read full review	No answers on this topic
Pros	Scalable and truly non-relational data HBase operations run in real-time on its database rather than MapReduce jobs Scales linearly to support billions of rows with millions of columns Incentivized Bharadwaj (Brad) Chivukula Director Of Engineering/Head of Reliability Engineering Read full review	No answers on this topic
Cons	Write performance Performance support for parquet file format. supports, but performance wise still not there API / library availability for spark, rather than creating a new library for it Incentivized Anson Abraham Data Lord Read full review	No answers on this topic
Likelihood to Renew	There's really not anything else out there that I've seen comparable for my use cases. HBase has never proven me wrong. Some companies align their whole business on HBase and are moving all of their infrastructure from other database engines to HBase. It's also open source and has a very collaborative community. Incentivized Verified User Anonymous Read full review	No answers on this topic
Alternatives Considered	Compared NoSQL databases with traditional databases for faster retrieval and consistency. As MongoDB is a NoSQL supports dynamic fields, however, query performance is bad for aggregations and added maintenance. When compared with MySQL and Teradata, it could not scale up as fast as Hbase and added cost involved to it. HBase can be easily scalable to a huge volume of records, have a faster lookup and provides consistency Incentivized Vinaybabu Raghunandha Naidu Software Engineer - Big Data Platform Read full review	No answers on this topic
Return on Investment	Positive: Open source, easy to use, good to store big data. Negative: SQL functionalities are not available. More memory utilization More troubleshooting Incentivized RAVI MISHRA Data Engineer Read full review	No answers on this topic
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