Apache HBase vs. FirebirdSQL

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
Firebird
Score 9.8 out of 10
N/A
FirebirdSQL is an open-source database which can be embedded.N/A
Pricing
Apache HBaseFirebirdSQL
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
HBaseFirebird
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
Community Pulse
Apache HBaseFirebirdSQL
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.
Firebird
Chose Firebird
It is cost-effective, maintenance-free, easy to deploy and use on Linux and Windows environments and it works steadily. It has an open-source license. Installing Oracle was quite difficult in comparison to Firebird.
Chose Firebird
It came a time when the practice of SQLite was lagging behind and of course, we were looking at the cost that was being involved and so Firebird made the breakthrough for us from both. It has an open-source license and it is easy to deploy on Windows and Linux environments.
Chose Firebird
As you know, the version of an application is very good for a period in the world of information technologies, it is the first in the performance / cost table. But some periods come and that practice lags behind. When Firebird made such a breakthrough, we preferred this …
Chose Firebird
Back then I evaluated Oracle 8, IBM DB2, Mimer, SAP DB, MySQL, Borland Interbase (not Embarcadero Interbase and that one has the same roots as Firebird) and most likely other RDBMS. Firebird was free, usage was ok, it was (for my application) maintenance free and speed was ok …
Features
Apache HBaseFirebirdSQL
NoSQL Databases
Comparison of NoSQL Databases features of Product A and Product B
Apache HBase
7.7
Ratings
14% below category average
FirebirdSQL
-
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 HBaseFirebirdSQL
Small Businesses
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
InfluxDB
InfluxDB
Score 8.8 out of 10
Medium-sized Companies
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
SQLite
SQLite
Score 9.6 out of 10
Enterprises
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
SQLite
SQLite
Score 9.6 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache HBaseFirebirdSQL
Likelihood to Recommend
7.7
(0 ratings)
8.2
(0 ratings)
Likelihood to Renew
7.9
(0 ratings)
9.0
(0 ratings)
Usability
-
(0 ratings)
8.0
(0 ratings)
Support Rating
-
(0 ratings)
5.0
(0 ratings)
Implementation Rating
-
(0 ratings)
9.0
(0 ratings)
User Testimonials
Apache HBaseFirebirdSQL
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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When looking for low maintenance and a solution suited for all kinds of pc applications. It is great when you are looking to store physical files in folder locations and you can then reference the document in the database. It has an open-source community around it along with documentation for third-party drivers of the development environment.
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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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  • Reliable RDMS for the SMB's and we found its performance is really fast.
  • It allows us to store the physical files into the folder location and reference of the document in the database.
  • Easy to take back-ups, and portable.
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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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  • Clustering features require alot of attention.
  • Remote access can be quite slow.
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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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Because it is free and usually zero maintenance. Just the issue of more difficult format updates in the future lower the rating a bit.
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Usability
No answers on this topic
Usability has improved by unifying the architecture. The only thing's missing out of the box is a simple GUI DB tool for viewing DB contents and maybe running some SQL queries.
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Support Rating
No answers on this topic
This is an open source project. It provides a fair amount of free documentation and I think forums somewhere...
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Implementation Rating
No answers on this topic
Even somebody just starting to use RDBMS himself should get it working quickly, at least if he's got a GUI tool and some SQL knowledge.
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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
Read full review
It is cost-effective, maintenance-free, easy to deploy and use on Linux and Windows environments and it works steadily. It has an open-source license. Installing Oracle was quite difficult in comparison to Firebird.
Read full review
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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  • The return on investment was of course because it freed us from paid relational databases.
  • We have never experienced a negative situation.
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