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DBMS > Cassandra vs. Spark SQL vs. YugabyteDB

System Properties Comparison Cassandra vs. Spark SQL vs. YugabyteDB

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Editorial information provided by DB-Engines
NameCassandra  Xexclude from comparisonSpark SQL  Xexclude from comparisonYugabyteDB  Xexclude from comparison
DescriptionWide-column store based on ideas of BigTable and DynamoDB infoOptimized for write accessSpark SQL is a component on top of 'Spark Core' for structured data processingHigh-performance distributed SQL database for global, internet-scale applications. Wire compatible with PostgreSQL.
Primary database modelWide column storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score119.18
Rank#10  Overall
#1  Wide column stores
Score18.63
Rank#34  Overall
#21  Relational DBMS
Score1.14
Rank#158  Overall
#77  Relational DBMS
Websitecassandra.apache.orgspark.apache.org/­sqlwww.yugabyte.com
Technical documentationcassandra.apache.org/­doc/­latestspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.yugabyte.com
github.com/­yugabyte/­yugabyte-db
DeveloperApache Software Foundation infoApache top level project, originally developped by FacebookApache Software FoundationYugabyte Inc.
Initial release200820142017
Current release3.11.8, August 20203.0.1, October 20202.2.0, July 2020
License infoCommercial or Open SourceOpen Source infoApache version 2Open Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScalaC and C++
Server operating systemsBSD
Linux
OS X
Windows
Linux
OS X
Windows
Linux
OS X
Data schemeschema-freeyesdepending on used data model
Typing infopredefined data types such as float or dateyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonono
Secondary indexesrestricted infoonly equality queries, not always the best performing solutionnoyes
SQL infoSupport of SQLSQL-like SELECT, DML and DDL statements (CQL)SQL-like DML and DDL statementsyes, PostgreSQL compatible
APIs and other access methodsProprietary protocol infoCQL (Cassandra Query Language, an SQL-like language)
Thrift
JDBC
ODBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
Supported programming languagesC#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript infoNode.js
Perl
PHP
Python
Ruby
Scala
Java
Python
R
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresnonoyes infosql, plpgsql, C
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infono "single point of failure"yes, utilizing Spark CoreHash and Range Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infoRepresentation of geographical distribution of servers is possiblenoneBased on Raft distributed consensus protocol, minimum 3 replicas for continuous availability
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be individually decided for each write operation
Strong consistency on writes and tunable consistency on reads
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoAtomicity and isolation are supported for single operationsnoDistributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infobased on RocksDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlAccess rights for users can be defined per objectnoyes
More information provided by the system vendor
CassandraSpark SQLYugabyteDB
Specific characteristicsApache Cassandra is the leading NoSQL, distributed database management system, well...
» more
Gain Developer Agility Leverage full power of PostgreSQL-compatible SQL and distributed...
» more
Competitive advantagesNo single point of failure ensures 100% availability . Operational simplicity for...
» more
YugabyteDB is a distributed ACID-compliant database that brings together four must-have...
» more
Typical application scenariosInternet of Things (IOT), fraud detection applications, recommendation engines, product...
» more
YugabyteDB is a good fit for fast-growing, cloud native applications that need to...
» more
Key customersApple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
» more
Market metricsCassandra is used by 40% of the Fortune 100.
» more
Licensing and pricing modelsApache license  Pricing for commercial distributions provided by DataStax and available...
» more
YugabyteDB is a 100% open source project licensed under the permissive Apache 2.0...
» more

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DBHawk: Secure access to SQL, NoSQL and Cloud databases with an all-in-one solution.
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Instaclustr: Hosted & Managed Apache Cassandra as a Service
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DataStax Enterprise: Apache Cassandra for enterprises.
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More resources
CassandraSpark SQLYugabyteDB
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