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DBMS > EJDB vs. NSDb vs. Spark SQL vs. TDSQL for MySQL

System Properties Comparison EJDB vs. NSDb vs. Spark SQL vs. TDSQL for MySQL

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Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonNSDb  Xexclude from comparisonSpark SQL  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparison
DescriptionEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Scalable, 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 processingA high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.
Primary database modelDocument storeTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.31
Rank#296  Overall
#44  Document stores
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.85
Rank#207  Overall
#97  Relational DBMS
Websitegithub.com/­Softmotions/­ejdbnsdb.iospark.apache.org/­sqlwww.tencentcloud.com/­products/­dcdb
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdnsdb.io/­Architecturespark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.tencentcloud.com/­document/­product/­1042
DeveloperSoftmotionsApache Software FoundationTencent
Initial release2012201720142013
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoGPLv2Open Source infoApache Version 2.0Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJava, ScalaScala
Server operating systemsserver-lessLinux
macOS
Linux
OS X
Windows
hosted
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idyes: int, bigint, decimal, stringyesyes
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 indexesnoall fields are automatically indexednoyes
SQL infoSupport of SQLnoSQL-like query languageSQL-like DML and DDL statementsyes
APIs and other access methodsin-process shared librarygRPC
HTTP REST
WebSocket
JDBC
ODBC
JDBC
ODBC
Supported programming languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
Java
Scala
Java
Python
R
Scala
C
C#
C++
Java
PHP
Python
Ruby
Server-side scripts infoStored proceduresnononoyes
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark CoreAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possiblenonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/Write Lockingyesyesyes
Durability infoSupport for making data persistentyesUsing Apache Luceneyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlnonoUsers with fine-grained authorization concept

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More resources
EJDBNSDbSpark SQLTDSQL for MySQL
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