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DBMS > Datastax Enterprise vs. Datomic vs. NSDb vs. Spark SQL

System Properties Comparison Datastax Enterprise vs. Datomic vs. NSDb vs. Spark SQL

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Editorial information provided by DB-Engines
NameDatastax Enterprise  Xexclude from comparisonDatomic  Xexclude from comparisonNSDb  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionDataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelWide column storeRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.80
Rank#60  Overall
#4  Wide column stores
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.datastax.com/­products/­datastax-enterprisewww.datomic.comnsdb.iospark.apache.org/­sql
Technical documentationdocs.datastax.comdocs.datomic.comnsdb.io/­Architecturespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDataStaxCognitectApache Software Foundation
Initial release2011201220172014
Current release6.8, April 20201.0.6735, June 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freeOpen Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.
Implementation languageJavaJava, ClojureJava, ScalaScala
Server operating systemsLinux
OS X
All OS with a Java VMLinux
macOS
Linux
OS X
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes: int, bigint, decimal, stringyes
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.nononono
Secondary indexesyesyesall fields are automatically indexedno
SQL infoSupport of SQLSQL-like DML and DDL statements (CQL); Spark SQLnoSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsProprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
RESTful HTTP APIgRPC
HTTP REST
WebSocket
JDBC
ODBC
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Clojure
Java
Java
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsnono
TriggersyesBy using transaction functionsno
Partitioning methods infoMethods for storing different data on different nodesSharding infono "single point of failure"none infoBut extensive use of caching in the application peersShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesconfigurable replication factor, datacenter aware, advanced replication for edge computingnone infoBut extensive use of caching in the application peersnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoAtomicity and isolation are supported for single operationsACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)Using Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes inforecommended only for testing and developmentno
User concepts infoAccess controlAccess rights for users can be defined per objectnono
More information provided by the system vendor
Datastax EnterpriseDatomicNSDbSpark SQL
Specific characteristicsDataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more
Competitive advantagesSupporting the following application requirements: Zero downtime - Built on Apache...
» more
Typical application scenariosApplications that must be massively and linearly scalable with 100% uptime and able...
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Key customersCapital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more
Market metricsAmong the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more
Licensing and pricing modelsAnnual subscription
» more

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Datastax EnterpriseDatomicNSDbSpark SQL
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