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DBMS > NSDb vs. RavenDB vs. Spark SQL vs. Teradata Aster

System Properties Comparison NSDb vs. RavenDB vs. Spark SQL vs. Teradata Aster

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Editorial information provided by DB-Engines
NameNSDb  Xexclude from comparisonRavenDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseSpark SQL is a component on top of 'Spark Core' for structured data processingPlatform for big data analytics on multistructured data sources and types
Primary database modelTime Series DBMSDocument storeRelational DBMSRelational DBMS
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Score2.84
Rank#101  Overall
#18  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitensdb.ioravendb.netspark.apache.org/­sql
Technical documentationnsdb.io/­Architectureravendb.net/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperHibernating RhinosApache Software FoundationTeradata
Initial release2017201020142005
Current release5.4, July 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL version 3, commercial license availableOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ScalaC#Scala
Server operating systemsLinux
macOS
Linux
macOS
Raspberry Pi
Windows
Linux
OS X
Windows
Linux
Data schemeschema-freeyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyes: int, bigint, decimal, stringnoyesyes
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.nonoyes infoin Aster File Store
Secondary indexesall fields are automatically indexedyesnoyes
SQL infoSupport of SQLSQL-like query languageSQL-like query language (RQL)SQL-like DML and DDL statementsyes
APIs and other access methodsgRPC
HTTP REST
WebSocket
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
JDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesJava
Scala
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnoyesnoR packages
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationnoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID, Cluster-wide transaction availablenoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentUsing Apache Luceneyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAuthorization levels configured per client per databasenofine grained access rights according to SQL-standard

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More resources
NSDbRavenDBSpark SQLTeradata Aster
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