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DBMS > EsgynDB vs. GridGain vs. NSDb vs. RisingWave

System Properties Comparison EsgynDB vs. GridGain vs. NSDb vs. RisingWave

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGridGain  Xexclude from comparisonNSDb  Xexclude from comparisonRisingWave  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGridGain is an in-memory computing platform, built on Apache IgniteScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesA distributed RDBMS for stream processing, wire-compatible with PostgreSQL
Primary database modelRelational DBMSKey-value store
Relational DBMS
Time Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score0.58
Rank#242  Overall
#111  Relational DBMS
Websitewww.esgyn.cnwww.gridgain.comnsdb.iowww.risingwave.com/­database
Technical documentationwww.gridgain.com/­docs/­index.htmlnsdb.io/­Architecturedocs.risingwave.com/­docs/­current/­intro
DeveloperEsgynGridGain Systems, Inc.RisingWave Labs
Initial release2015200720172022
Current releaseGridGain 8.5.11.2, September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2.0
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.
Implementation languageC++, JavaJava, C++, .NetJava, ScalaRust
Server operating systemsLinuxLinux
OS X
Solaris
Windows
Linux
macOS
Docker
Linux
macOS
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes: int, bigint, decimal, stringStandard SQL-types and JSON
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.noyesnono
Secondary indexesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLyesANSI-99 for query and DML statements, subset of DDLSQL-like query languageyes
APIs and other access methodsADO.NET
JDBC
ODBC
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
gRPC
HTTP REST
WebSocket
JDBC
PostgreSQL wire protocol
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Java
PHP
Python
Ruby
Scala
Java
Scala
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresJava Stored Proceduresyes (compute grid and cache interceptors can be used instead)noUDFs in Python or Java
Triggersnoyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersyes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardSecurity Hooks for custom implementationsUsers and Roles

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More resources
EsgynDBGridGainNSDbRisingWave
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