DBMS > Cassandra vs. Hypertable vs. YugabyteDB

System Properties Comparison Cassandra vs. Hypertable vs. YugabyteDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

An open source BigTable implementation based on distributed file systems such as Hadoop

High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.

Primary database model

Wide column store

Relational DBMS

Secondary database models

Document store
Wide column store

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	118.15
Rank	#11	Overall
	#1	Wide column stores

Score	3.52
Rank	#97	Overall
	#51	Relational DBMS

Website

cassandra.apache.org

www.yugabyte.com

Technical documentation

cassandra.apache.org/doc/latest

docs.yugabyte.com
github.com/yugabyte/yugabyte-db

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Hypertable Inc.

Yugabyte Inc.

Initial release

2008

2009

2017

Current release

4.0.5, July 2022

0.9.8.11, March 2016

2.14, July 2022

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

GNU version 3. Commercial license available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.
Aiven for Apache Cassandra: Fully managed, open source NoSQL database specifically designed to be highly available, performant, and scalable.

Yugabyte Cloud is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.

Implementation language

Java

C++

C and C++

Server operating systems

BSD
Linux
OS X
Windows

Linux
OS X
Windows

an inofficial Windows port is available

Linux
OS X

Data scheme

schema-free

depending on used data model

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

restricted

only equality queries, not always the best performing solution

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL-like SELECT, DML and DDL statements (CQL)

yes, PostgreSQL compatible

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

C++ API
Thrift

JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

C++
Java
Perl
PHP
Python
Ruby

C
C#
C++
Go
Java
JavaScript (Node.js)
Python
Ruby

Server-side scripts

Stored procedures

yes

sql, plpgsql, C

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

Hash and Range Sharding, row-level geo-partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

selectable replication factor on file system level

Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

Strong consistency on writes and tunable consistency on reads

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomicity and isolation are supported for single operations

Distributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

based on RocksDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Access rights for users can be defined per object

yes

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
» more

YugabyteDB is an open source distributed SQL database for cloud native transactional...
» more

Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
» more

PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
» more

Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
» more

Systems of record and engagement for cloud native applications that require resilience,...
» more

Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
» more

Market metrics

Cassandra is used by 40% of the Fortune 100.
» more

900,000+ lifetime clusters deployed 5.5K+ GitHub stars 4.3K+ YugabyteDB Community...
» more

Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
» more

Apache 2.0 license for the database
» more

News

PacketFabric's Anna Claiborne and Dave Ward: Building Strong Networks with Guts and Vision
10 August 2022

Real-World Machine Learning with Apache Cassandra and Apache Spark (Part 2)
2 August 2022

Creating A Safer Internet One Hacker at a Time with Marten Mickos of HackerOne
27 July 2022

Migrating from SQL to NoSQL with Spring PetClinic and Apache Cassandra
26 July 2022

Pulling Real-Time Ethereum Transactions with Web3.js
20 July 2022

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.