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DBMS > ScyllaDB vs. Spark SQL vs. Sphinx vs. Splice Machine

System Properties Comparison ScyllaDB vs. Spark SQL vs. Sphinx vs. Splice Machine

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Editorial information provided by DB-Engines
NameScyllaDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionCassandra and DynamoDB compatible wide column storeSpark SQL is a component on top of 'Spark Core' for structured data processingOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelWide column storeRelational DBMSSearch engineRelational DBMS
Secondary database modelsKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.75
Rank#68  Overall
#5  Wide column stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.scylladb.comspark.apache.org/­sqlsphinxsearch.comsplicemachine.com
Technical documentationdocs.scylladb.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperScyllaDBApache Software FoundationSphinx Technologies Inc.Splice Machine
Initial release2015201420012014
Current releaseScyllaDB Open Source 5.4.1, January 20243.5.0 ( 2.13), September 20233.5.1, February 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoOpen Source (AGPL), commercial license availableOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Scylla Cloud: Create real-time applications that run at global scale with Scylla Cloud, the industry’s most powerful NoSQL DBaaS
Implementation languageC++ScalaC++Java
Server operating systemsLinuxLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.nono
Secondary indexesyes infocluster global secondary indicesnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like DML and DDL statements (CQL)SQL-like DML and DDL statementsSQL-like query language (SphinxQL)yes
APIs and other access methodsProprietary protocol (CQL) infocompatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift
JDBC
ODBC
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesFor CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby
Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes, Luanonoyes infoJava
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infoRepresentation of geographical distribution of servers is possiblenonenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Tunable Consistency infocan be individually decided for each write operation
Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoAtomicity and isolation are supported for single operationsnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoin-memory tablesnoyes
User concepts infoAccess controlAccess rights for users can be defined per objectnonoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
ScyllaDBSpark SQLSphinxSplice Machine
Specific characteristicsScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
» more
Competitive advantagesHighly-performant (efficiently utilizes full resources of a node and network; millions...
» more
Typical application scenariosScyllaDB is ideal for applications that require high throughput and low latency at...
» more
Key customersDiscord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
» more
Market metricsScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
» more
Licensing and pricing modelsScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
» more

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ScyllaDBSpark SQLSphinxSplice Machine
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