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DBMS > OpenQM vs. ScyllaDB vs. Spark SQL vs. Sphinx

System Properties Comparison OpenQM vs. ScyllaDB vs. Spark SQL vs. Sphinx

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Editorial information provided by DB-Engines
NameOpenQM infoalso called QM  Xexclude from comparisonScyllaDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionQpenQM is a high-performance, self-tuning, multi-value DBMSCassandra 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 databases
Primary database modelMultivalue DBMSWide column storeRelational DBMSSearch engine
Secondary database modelsKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.34
Rank#284  Overall
#10  Multivalue DBMS
Score4.08
Rank#76  Overall
#5  Wide column stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitewww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-open-qmwww.scylladb.comspark.apache.org/­sqlsphinxsearch.com
Technical documentationdocs.scylladb.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docs
DeveloperRocket Software, originally Martin PhillipsScyllaDBApache Software FoundationSphinx Technologies Inc.
Initial release1993201520142001
Current release3.4-12ScyllaDB Open Source 5.4.1, January 20243.5.0 ( 2.13), September 20233.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoGPLv2, extended commercial license availableOpen Source infoOpen Source (AGPL), commercial license availableOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Scylla Cloud: Create real-time applications that run at global scale with Scylla Cloud, the industry’s most powerful NoSQL DBaaS
Implementation languageC++ScalaC++
Server operating systemsAIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows
LinuxLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyes infowith some exceptionsschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesno
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.yesnono
Secondary indexesyesyes infocluster global secondary indicesnoyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-like DML and DDL statements (CQL)SQL-like DML and DDL statementsSQL-like query language (SphinxQL)
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 protocol
Supported programming languages.Net
Basic
C
Java
Objective C
PHP
Python
For 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
Server-side scripts infoStored proceduresyesyes, Luanono
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesyesShardingyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor infoRepresentation of geographical distribution of servers is possiblenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Tunable Consistency infocan be individually decided for each write operation
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoAtomicity and isolation are supported for single operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoin-memory tablesno
User concepts infoAccess controlAccess rights can be defined down to the item levelAccess rights for users can be defined per objectnono
More information provided by the system vendor
OpenQM infoalso called QMScyllaDBSpark SQLSphinx
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...
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Typical application scenariosScyllaDB is ideal for applications that require high throughput and low latency at...
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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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OpenQM infoalso called QMScyllaDBSpark SQLSphinx
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