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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    HBase

    Score7.3 out of 10
    N/AThe 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

    Elasticsearch

    Score8.6 out of 10
    N/AElasticsearch is an enterprise search tool from Elastic in Mountain View, California.

    $16

    per month

    Pricing
    HBaseElasticsearch
    Editions & Modules
    No answers on this topic
    Standard
    $16.00
    per month
    Gold
    $19.00
    per month
    Platinum
    $22.00
    per month
    Enterprise
    Contact Sales
    Offerings
    Pricing Offerings
    HBaseElasticsearch
    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
    HBaseElasticsearch
    Considered Both Products
    Apache
    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
    Elastic
    Chose Elasticsearch
    We have used Solr. Elastic Search aggregations is what made us move to elastic search initially.
    Incentivized
    Chose Elasticsearch
    Ability to support JSON queries, Percolator, ease to set up and custom routing were some of the reasons why we decided to use Elasticsearch instead of Solr.
    Incentivized
    Key User Insights
    Would buy again
    No answers on this topic
    82%
    Would buy again
    14 Answers
    Delivers good value for the price
    No answers on this topic
    100%
    Delivers good value for the price
    16 Answers
    Happy with the feature set
    No answers on this topic
    100%
    Happy with the feature set
    17 Answers
    Lived up to sales and marketing promises
    No answers on this topic
    100%
    Lived up to sales and marketing promises
    13 Answers
    Implementation went as expected
    No answers on this topic
    87%
    Implementation went as expected
    13 Answers
    Features
    HBaseElasticsearch
    NoSQL Databases
    Comparison of NoSQL Databases features of Apache HBase and Elasticsearch
    Feature
    Apache HBase
    7.7
    5 Ratings
    14% below category average
    Elasticsearch
    -
    Ratings
    Performance7.15 Ratings00 Ratings
    Availability7.85 Ratings00 Ratings
    Concurrency7.05 Ratings00 Ratings
    Security7.85 Ratings00 Ratings
    Scalability8.65 Ratings00 Ratings
    Data model flexibility7.15 Ratings00 Ratings
    Deployment model flexibility8.25 Ratings00 Ratings
    Best Alternatives
    HBaseElasticsearch
    Small Businesses
    Redis Software
    Score8.3 out of 10
    Apache Solr
    Score9 out of 10
    Medium-sized Companies
    IBM Cloudant
    Score7.4 out of 10
    Algolia
    Score8.7 out of 10
    Enterprises
    IBM Cloudant
    Score7.4 out of 10
    Algolia
    Score8.7 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    HBaseElasticsearch
    Likelihood to Recommend
    7.7
    (10 ratings)
    9.0
    (48 ratings)
    Likelihood to Renew
    7.9
    (10 ratings)
    10.0
    (1 ratings)
    Usability
    -
    (0 ratings)
    10.0
    (1 ratings)
    Support Rating
    -
    (0 ratings)
    7.8
    (9 ratings)
    Implementation Rating
    -
    (0 ratings)
    9.0
    (1 ratings)
    User Testimonials
    HBaseElasticsearch
    Likelihood to Recommend
    Apache
    Hbase is well suited for large organizations with millions of operations performing on tables, real-time lookup of records in a table, range queries, random reads and writes and online analytics operations. Hbase cannot be replaced for traditional databases as it cannot support all the features, CPU and memory intensive. Observed increased latency when using with MapReduce job joins.
    Incentivized
    Read full review
    Elastic
    Elasticsearch is a really scalable solution that can fit a lot of needs, but the bigger and/or those needs become, the more understanding & infrastructure you will need for your instance to be running correctly. Elasticsearch is not problem-free - you can get yourself in a lot of trouble if you are not following good practices and/or if are not managing the cluster correctly. Licensing is a big decision point here as Elasticsearch is a middleware component - be sure to read the licensing agreement of the version you want to try before you commit to it. Same goes for long-term support - be sure to keep yourself in the know for this aspect you may end up stuck with an unpatched version for years.
    Incentivized
    Read full review
    Pros
    Apache
    • Scalability. HBase can scale to trillions of records.
    • Fast. HBase is extremely fast to scan values or retrieve individual records by key.
    • HBase can be accessed by standard SQL via Apache Phoenix.
    • Integrated. I can easily store and retrieve data from HBase using Apache Spark.
    • It is easy to set up DR and backups.
    • Ingest. It is easy to ingest data into HBase via shell, Java, Apache NiFi, Storm, Spark, Flink, Python and other means.
    Incentivized
    Read full review
    Elastic
    • As I mentioned before, Elasticsearch's flexible data model is unparalleled. You can nest fields as deeply as you want, have as many fields as you want, but whatever you want in those fields (as long as it stays the same type), and all of it will be searchable and you don't need to even declare a schema beforehand!
    • Elastic, the company behind Elasticsearch, is super strong financially and they have a great team of devs and product managers working on Elasticsearch. When I first started using ES 3 years ago, I was 90% impressed and knew it would be a good fit. 3 years later, I am 200% impressed and blown away by how far it has come and gotten even better. If there are features that are missing or you don't think it's fast enough right now, I bet it'll be suitable next year because the team behind it is so dang fast!
    • Elasticsearch is really, really stable. It takes a lot to bring down a cluster. It's self-balancing algorithms, leader-election system, self-healing properties are state of the art. We've never seen network failures or hard-drive corruption or CPU bugs bring down an ES cluster.
    Incentivized
    Read full review
    Cons
    Apache
    • There are very few commands in HBase.
    • Stored procedures functionality is not available so it should be implemented.
    • HBase is CPU and Memory intensive with large sequential input or output access while as Map Reduce jobs are primarily input or output bound with fixed memory. HBase integrated with Map-reduce jobs will result in random latencies.
    Incentivized
    Read full review
    Elastic
    • Joining data requires duplicate de-normalized documents that make parent child relationships. It is hard and requires a lot of synchronizations
    • Tracking errors in the data in the logs can be hard, and sometimes recurring errors blow up the error logs
    • Schema changes require complete reindexing of an index
    Incentivized
    Read full review
    Likelihood to Renew
    Apache
    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
    Read full review
    Elastic
    We're pretty heavily invested in ElasticSearch at this point, and there aren't any obvious negatives that would make us reconsider this decision.
    Incentivized
    Read full review
    Usability
    Apache
    No answers on this topic
    Elastic
    To get started with Elasticsearch, you don't have to get very involved in configuring what really is an incredibly complex system under the hood. You simply install the package, run the service, and you're immediately able to begin using it. You don't need to learn any sort of query language to add data to Elasticsearch or perform some basic searching. If you're used to any sort of RESTful API, getting started with Elasticsearch is a breeze. If you've never interacted with a RESTful API directly, the journey may be a little more bumpy. Overall, though, it's incredibly simple to use for what it's doing under the covers.
    Incentivized
    Read full review
    Support Rating
    Apache
    No answers on this topic
    Elastic
    We've only used it as an opensource tooling. We did not purchase any additional support to roll out the elasticsearch software. When rolling out the application on our platform we've used the documentation which was available online. During our test phases we did not experience any bugs or issues so we did not rely on support at all.
    Incentivized
    Read full review
    Implementation Rating
    Apache
    No answers on this topic
    Elastic
    Do not mix data and master roles. Dedicate at least 3 nodes just for Master
    Incentivized
    Read full review
    Alternatives Considered
    Apache
    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 to an extent. HA between the two are almost the same.
    Incentivized
    Read full review
    Elastic
    As far as we are concerned, Elasticsearch is the gold standard and we have barely evaluated any alternatives. You could consider it an alternative to a relational or NoSQL database, so in cases where those suffice, you don't need Elasticsearch. But if you want powerful text-based search capabilities across large data sets, Elasticsearch is the way to go.
    Incentivized
    Read full review
    Return on Investment
    Apache
    • As Hbase is a noSql database, here we don't have transaction support and we cannot do many operations on the data.
    • Not having the feature of primary or a composite primary key is an issue as the architecture to be defined cannot be the same legacy type. Also the transaction concept is not applicable here.
    • The way data is printed on console is not so user-friendly. So we had to use some abstraction over HBase (eg apache phoenix) which means there is one new component to handle.
    Incentivized
    Read full review
    Elastic
    • We have had great luck with implementing Elasticsearch for our search and analytics use cases.
    • While the operational burden is not minimal, operating a cluster of servers, using a custom query language, writing Elasticsearch-specific bulk insert code, the performance and the relative operational ease of Elasticsearch are unparalleled.
    • We've easily saved hundreds of thousands of dollars implementing Elasticsearch vs. RDBMS vs. other no-SQL solutions for our specific set of problems.
    Incentivized
    Read full review
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