Apache HBase vs. Astra DB

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
Astra DB
Score 8.3 out of 10
N/A
Astra DB from DataStax is a vector database for developers that need to get accurate Generative AI applications into production, fast.N/A
Pricing
Apache HBaseAstra DB
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
HBaseAstra DB
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoYes
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Apache HBaseAstra DB
Top Pros

No answers on this topic

Top Cons

No answers on this topic

Features
Apache HBaseAstra DB
NoSQL Databases
Comparison of NoSQL Databases features of Product A and Product B
Apache HBase
7.7
5 Ratings
13% below category average
Astra DB
-
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
Vector Database
Comparison of Vector Database features of Product A and Product B
Apache HBase
-
Ratings
Astra DB
6.9
1 Ratings
0% below category average
Vector Data Connection00 Ratings7.31 Ratings
Vector Data Editing00 Ratings8.21 Ratings
Attribute Management00 Ratings5.51 Ratings
Geospatial Analysis00 Ratings8.21 Ratings
Geometric Transformations00 Ratings7.31 Ratings
Vector Data Visualization00 Ratings7.31 Ratings
Coordinate Reference System Management:00 Ratings6.41 Ratings
Data Import/Export00 Ratings6.41 Ratings
Symbolization and Styling00 Ratings7.31 Ratings
Data Sharing and Collaboration00 Ratings5.51 Ratings
Best Alternatives
Apache HBaseAstra DB
Small Businesses
IBM Cloudant
IBM Cloudant
Score 8.3 out of 10
SingleStore
SingleStore
Score 9.8 out of 10
Medium-sized Companies
IBM Cloudant
IBM Cloudant
Score 8.3 out of 10
SingleStore
SingleStore
Score 9.8 out of 10
Enterprises
IBM Cloudant
IBM Cloudant
Score 8.3 out of 10
SingleStore
SingleStore
Score 9.8 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache HBaseAstra DB
Likelihood to Recommend
7.7
(10 ratings)
8.3
(32 ratings)
Likelihood to Renew
7.9
(10 ratings)
-
(0 ratings)
Usability
-
(0 ratings)
7.8
(4 ratings)
Support Rating
-
(0 ratings)
8.9
(4 ratings)
Product Scalability
-
(0 ratings)
8.5
(30 ratings)
User Testimonials
Apache HBaseAstra DB
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.
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DataStax
I would start with the scenarios which are well-suited. I can see Antra DB excels at the scalability and global distribution part as with the company's continuously growing size, we need our data to be growing at the same speed, which ASTRA DB largely supports, and if we talk about the less appropriate scenario, I would say when we need to incorporate external tools for the better monitor, it sorts of fails purpose.
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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.
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DataStax
  • It's very resilient and scalable, no downtime and no issues scaling up to meet our needs.
  • Low latency reads and writes
  • Cost effective - The on demand model worked out cheaper than running our own clusters
  • Great support for any of our questions or issues
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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.
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DataStax
  • Need better fine-grained Security options.
  • The support team sometimes requires the escalate button pressed on tickets, to get timely responses. I will say, once the ticket is escalated, action is taken.
  • They require better documentation on the migration of data. The three primary methods for migrating large data volumes are bulk, Cassandra Data Migrator, and ZDM (Zero Downtime Migration Utility). Over time I have become very familiar will all three of these methods; however, through working with the Services team and the support team, it seemed like we were breaking new ground. I feel if the utilities were better documented and included some examples and/or use cases from large data migrations; this process would have been easier. One lesson learned is you likely need to migrate your application servers to the same cloud provider you host Astra on; otherwise, the latency is too large for latency-sensitive applications.
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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.
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DataStax
No answers on this topic
Usability
Apache
No answers on this topic
DataStax
It's a great product but suffers with counters. This isn't a deal breaker but lets down what is otherwise a good all round solution
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Support Rating
Apache
No answers on this topic
DataStax
Their response time is fast, in case you do not contact them during business hours, they give a very good follow-up to your case. They also facilitate video calls if necessary for debugging.
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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.
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DataStax
Graph, search, analytics, administration, developer tooling, and monitoring are all incorporated into a single platform by Astra DB. Mongo Db is a self-managed infrastructure. Astra DB has Wide column store and Mongo DB has Document store. The best thing is that Astra DB operates on Java while Mongo DB operates on C++
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Scalability
Apache
No answers on this topic
DataStax
We are well aware of the Cassandra architecture and familiar with the open source tooling that Datastax provides the industry (K8sSandra / Stargate) to scale Cassandra on Kubernetes.
Having prior knowledge of Cassandra / Kubernetes means we know that under the hood Astra is built on infinitely scalable technologies. We trust that the foundations that Astra is built on will scale so we know Astra will scale.
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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.
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DataStax
  • The high availability capabilities of Astra DB can assist in reducing downtime, which is crucial for revenue-generating applications.
  • The developer-friendly features of Astra DB, as well as support for known query languages, can help expedite development, save development time, and minimize labor costs. This can result in a shorter time to market and a higher ROI.
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