DBMS > EJDB vs. GridGain vs. Microsoft SQL Server vs. NuoDB vs. SingleStore

System Properties Comparison EJDB vs. GridGain vs. Microsoft SQL Server vs. NuoDB vs. SingleStore

Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

GridGain is an in-memory computing platform, built on Apache Ignite

Microsofts flagship relational DBMS

NuoDB is a webscale distributed database that supports SQL and ACID transactions

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Primary database model

Document store

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.13
Rank	#331	Overall
	#46	Document stores

Score	1.48
Rank	#150	Overall
	#1	Columnar
	#26	Key-value stores
	#2	Object oriented DBMS
	#69	Relational DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	0.87
Rank	#201	Overall
	#94	Relational DBMS

Score	4.02
Rank	#74	Overall
	#39	Relational DBMS

Website

github.com/Softmotions/ejdb

www.gridgain.com

www.microsoft.com/en-us/sql-server

www.3ds.com/nuodb-distributed-sql-database

www.singlestore.com

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

www.gridgain.com/docs/index.html

learn.microsoft.com/en-US/sql/sql-server

doc.nuodb.com

docs.singlestore.com

Developer

Softmotions

GridGain Systems, Inc.

Microsoft

Dassault Systèmes

originally NuoDB, Inc.

SingleStore Inc.

Initial release

2012

2007

1989

2013

Current release

GridGain 8.5.1

SQL Server 2022, November 2022

8.5, January 2024

License

Commercial or Open Source

Open Source

GPLv2

commercial, open source

commercial

restricted free version is available

commercial

limited edition free

commercial

free developer edition available

Cloud-based only

Only available as a cloud service

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Implementation language

Java, C++, .Net, Python, REST, SQL

C++

C++, Go

Server operating systems

server-less

Linux
OS X
Solaris
Windows
z/OS

Linux
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Linux

64 bit version required

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

yes

but no triggers and foreign keys

APIs and other access methods

in-process shared library

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

ADO.NET
JDBC
ODBC

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby

Bash
C
C#
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Java, SQL

yes

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

data is dynamically stored/cached on the nodes where it is read/written

Sharding

hash partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes (replicated cache)

yes, but depending on the SQL-Server Edition

yes

Managed transparently by NuoDB

Source-replica replication

stores two copies of each physical data partition on two separate nodes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

tunable commit protocol

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

MVCC

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Temporary table

yes

User concepts

Access control

Role-based access control
Security Hooks for custom implementations

fine grained access rights according to SQL-standard

Standard SQL roles/ privileges, Administrative Users

Fine grained access control via users, groups and roles

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