Apache HBase vs. GraphQL

Overview
ProductRatingMost Used ByProduct SummaryStarting 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
GraphQL
Score 7.0 out of 10
N/A
GraphQL is a query language for APIs and a runtime for fulfilling those queries with existing data. GraphQL provides an understandable description of the data in an API, to give clients the ability to ask for exactly what they need and nothing more, to make it easier to evolve APIs over time, and enables developer tools. It is free to use and open source under an MIT license.N/A
Pricing
Apache HBaseGraphQL
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
HBaseGraphQL
Free Trial
NoNo
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Apache HBaseGraphQL
Considered Both Products
HBase
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.
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 …
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 …
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 …
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 …
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.
GraphQL

No answer on this topic

Features
Apache HBaseGraphQL
NoSQL Databases
Comparison of NoSQL Databases features of Product A and Product B
Apache HBase
7.7
Ratings
14% below category average
GraphQL
-
Ratings
Performance7.10 Ratings00 Ratings
Availability7.80 Ratings00 Ratings
Concurrency7.00 Ratings00 Ratings
Security7.80 Ratings00 Ratings
Scalability8.60 Ratings00 Ratings
Data model flexibility7.10 Ratings00 Ratings
Deployment model flexibility8.20 Ratings00 Ratings
Best Alternatives
Apache HBaseGraphQL
Small Businesses
IBM Cloudant
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Score 7.4 out of 10
InfluxDB
InfluxDB
Score 9.0 out of 10
Medium-sized Companies
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
SQLite
SQLite
Score 8.0 out of 10
Enterprises
IBM Cloudant
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Score 7.4 out of 10
SQLite
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Score 8.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache HBaseGraphQL
Likelihood to Recommend
7.7
(0 ratings)
-
(0 ratings)
Likelihood to Renew
7.9
(0 ratings)
-
(0 ratings)
User Testimonials
Apache HBaseGraphQL
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.
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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
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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
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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.
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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
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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
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No answers on this topic
ScreenShots