Amazon Keyspaces vs. Apache HBase

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Amazon Keyspaces
Score 6.4 out of 10
N/A
Amazon Keyspaces (for Apache Cassandra) is a scalable, highly available, and managed Apache Cassandra–compatible database service. With Amazon Keyspaces, users can run Cassandra workloads on AWS using the same Cassandra application code and developer tools without having to provision, patch, or manage servers, or installing, maintaining, or operating software. Amazon Keyspaces is serverless, so users pay only for resources used and the service can automatically scale tables up and down in…N/A
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
Pricing
Amazon KeyspacesApache HBase
Editions & Modules
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Offerings
Pricing Offerings
Amazon KeyspacesHBase
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
Amazon KeyspacesApache HBase
Best Alternatives
Amazon KeyspacesApache HBase
Small Businesses

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Medium-sized Companies
Azure Cosmos DB
Azure Cosmos DB
Score 9.0 out of 10
Azure Cosmos DB
Azure Cosmos DB
Score 9.0 out of 10
Enterprises
Azure Cosmos DB
Azure Cosmos DB
Score 9.0 out of 10
Azure Cosmos DB
Azure Cosmos DB
Score 9.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Amazon KeyspacesApache HBase
Likelihood to Recommend
-
(0 ratings)
7.7
(10 ratings)
Likelihood to Renew
-
(0 ratings)
7.9
(10 ratings)
User Testimonials
Amazon KeyspacesApache HBase
Likelihood to Recommend
Amazon AWS
No answers on this topic
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.
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Pros
Amazon AWS
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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.
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Cons
Amazon AWS
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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.
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Likelihood to Renew
Amazon AWS
No answers on this topic
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.
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Alternatives Considered
Amazon AWS
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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.
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Return on Investment
Amazon AWS
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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.
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