What users are saying about
76 Ratings
81 Ratings
76 Ratings
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Score 7.9 out of 100
81 Ratings
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Score 7.9 out of 100

Likelihood to Recommend

Cassandra

Apache Cassandra is a NoSQL database and well suited where you need highly available, linearly scalable, tunable consistency and high performance across varying workloads. It has worked well for our use cases, and I shared my experiences to use it effectively at the last Cassandra summit! http://bit.ly/1Ok56TKIt is a NoSQL database, finally you can tune it to be strongly consistent and successfully use it as such. However those are not usual patterns, as you negotiate on latency. It works well if you require that. If your use case needs strongly consistent environments with semantics of a relational database or if the use case needs a data warehouse, or if you need NoSQL with ACID transactions, Apache Cassandra may not be the optimum choice.
Rekha Joshi | TrustRadius Reviewer

Apache Hive

Apache Hive shines for ad-hoc analysis and plugging into BI tools. Its SQL-like syntax allows for ease of use not for only for engineers but also for data analysts. Through our experience, there are probably more desirable tools to use if you are planning on integrating Hive into your processing pipeline.
Anonymous | TrustRadius Reviewer

Feature Rating Comparison

NoSQL Databases

Cassandra
8.0
Apache Hive
Performance
Cassandra
8.5
Apache Hive
Availability
Cassandra
8.7
Apache Hive
Concurrency
Cassandra
7.6
Apache Hive
Security
Cassandra
8.0
Apache Hive
Scalability
Cassandra
9.4
Apache Hive
Data model flexibility
Cassandra
6.7
Apache Hive
Deployment model flexibility
Cassandra
7.0
Apache Hive

Pros

Cassandra

  • Continuous availability: as a fully distributed database (no master nodes), we can update nodes with rolling restarts and accommodate minor outages without impacting our customer services.
  • Linear scalability: for every unit of compute that you add, you get an equivalent unit of capacity. The same application can scale from a single developer's laptop to a web-scale service with billions of rows in a table.
  • Amazing performance: if you design your data model correctly, bearing in mind the queries you need to answer, you can get answers in milliseconds.
  • Time-series data: Cassandra excels at recording, processing, and retrieving time-series data. It's a simple matter to version everything and simply record what happens, rather than going back and editing things. Then, you can compute things from the recorded history.
David Prinzing | TrustRadius Reviewer

Apache Hive

  • Hive syntax is almost like SQL, so for someone already familiar with SQL it takes almost no effort to pick up Hive.
  • To be able to run map reduce jobs using json parsing and generate dynamic partitions in parquet file format.
  • Simplifies your experience with Hadoop especially for non-technical/coding partners.
Bharadwaj (Brad) Chivukula | TrustRadius Reviewer

Cons

Cassandra

  • Cassandra runs on the JVM and therefor may require a lot of GC tuning for read/write intensive applications.
  • Requires manual periodic maintenance - for example it is recommended to run a cleanup on a regular basis.
  • There are a lot of knobs and buttons to configure the system. For many cases the default configuration will be sufficient, but if its not - you will need significant ramp up on the inner workings of Cassandra in order to effectively tune it.
Anonymous | TrustRadius Reviewer

Apache Hive

  • Use Hive for analytical work loads. Write once and read many scenarios. Do not prefer updates and deletes.
  • Behind scenes Hive creates map reduce jobs. Hive performance is slow compared to Apache Spark.
  • Map reduce writes the intermediate outputs to dial whereas Spark operates in in-memory and uses DAG.
Anonymous | TrustRadius Reviewer

Likelihood to Renew

Cassandra

Cassandra 8.6
Based on 16 answers
I would recommend Cassandra DB to those who know their use case very well, as well as know how they are going to store and retrieve data. If you need a guarantee in data storage and retrieval, and a DB that can be linearly grown by adding nodes across availability zones and regions, then this is the database you should choose.
Anonymous | TrustRadius Reviewer

Apache Hive

Apache Hive 10.0
Based on 1 answer
Since I do not know the second data warehouse solution that integrate with HDFS as well as Hive.
Yinghua Hu | TrustRadius Reviewer

Usability

Cassandra

Cassandra 7.0
Based on 1 answer
It’s great tool but it can be complicated when it comes administration and maintenance.
Glen Kim | TrustRadius Reviewer

Apache Hive

Apache Hive 8.5
Based on 9 answers
Thanks to its high usability Apache Hive enables users to craft extensive queries really efficiently and at the same time to how to hold response times very low. HiveQL simplicity makes it super easy to manage large datasets, what was almost an impossible task before introduction of Apache Hive data warehousing platform in our company.
Anonymous | TrustRadius Reviewer

Support Rating

Cassandra

Cassandra 7.0
Based on 2 answers
Sometimes instead giving straight answer, we ‘re getting transfered to talk professional service.
Glen Kim | TrustRadius Reviewer

Apache Hive

Apache Hive 7.1
Based on 8 answers
Hive also has a community platform of its own just like other Hadoop frameworks. Most of the queries/problems are resolved in the community itself. We can just post our problems or get in touch with a specific user and get the issue resolved. Otherwise there is always the product support team for any resolution.
Partha Protim Pegu | TrustRadius Reviewer

Alternatives Considered

Cassandra

We evaluated MongoDB also, but don't like the single point failure possibility. The HBase coupled us too tightly to the Hadoop world while we prefer more technical flexibility. Also HBase is designed for "cold"/old historical data lake use cases and is not typically used for web and mobile applications due to its performance concern. Cassandra, by contrast, offers the availability and performance necessary for developing highly available applications. Furthermore, the Hadoop technology stack is typically deployed in a single location, while in the big international enterprise context, we demand the feasibility for deployment across countries and continents, hence finally we are favor of Cassandra
yixiang Shan | TrustRadius Reviewer

Apache Hive

Besides Hive, I have used Google BigQuery, which is costly but have very high computation speed.Amazon Redshift is the another product, I used in my recent organisation.Both Redshift and BigQuery are managed solution whereas Hive needs to be managed
Manjeet Singh | TrustRadius Reviewer

Return on Investment

Cassandra

  • I have no experience with this but from the blogs and news what I believe is that in businesses where there is high demand for scalability, Cassandra is a good choice to go for.
  • Since it works on CQL, it is quite familiar with SQL in understanding therefore it does not prevent a new employee to start in learning and having the Cassandra experience at an industrial level.
Anonymous | TrustRadius Reviewer

Apache Hive

  • It exposes the distributed calculation world (Hadoop) to the users but doesn't require the user to have the in-depth understanding of boilerplate details, it reduces the time of learning and let the data analyst can focus their efforts on the core business.
Anonymous | TrustRadius Reviewer

Pricing Details

Cassandra

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No

Apache Hive

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No

Rating Summary

Likelihood to Recommend

Cassandra
6.8
Apache Hive
8.0

Likelihood to Renew

Cassandra
8.6
Apache Hive
10.0

Usability

Cassandra
7.0
Apache Hive
8.5

Support Rating

Cassandra
7.0
Apache Hive
7.1

Implementation Rating

Cassandra
7.0
Apache Hive

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