DBMS > EJDB vs. ITTIA vs. jBASE vs. Microsoft SQL Server vs. SingleStore

System Properties Comparison EJDB vs. ITTIA vs. jBASE vs. Microsoft SQL Server vs. SingleStore

Editorial information provided by DB-Engines

Name

Description

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

Edge Time Series DBMS with Real-Time Stream Processing

A robust multi-value DBMS comprising development tools and middleware

Microsofts flagship relational DBMS

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

Secondary database models

Relational DBMS

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	0.36
Rank	#272	Overall
	#22	Time Series DBMS

Score	1.36
Rank	#157	Overall
	#3	Multivalue DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	4.02
Rank	#74	Overall
	#39	Relational DBMS

Website

github.com/Softmotions/ejdb

www.ittia.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

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

www.singlestore.com

Technical documentation

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

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

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

docs.singlestore.com

Developer

Softmotions

ITTIA L.L.C.

Rocket Software (formerly Zumasys)

Microsoft

SingleStore Inc.

Initial release

2012

2007

1991

1989

2013

Current release

8.7

5.7

SQL Server 2022, November 2022

8.5, January 2024

License

Commercial or Open Source

Open Source

GPLv2

commercial

restricted free version is available

commercial

free developer edition available

Cloud-based only

Only available as a cloud service

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Implementation language

C and C++

C++

C++, Go

Server operating systems

server-less

Linux
Windows

AIX
Linux
Windows

Linux
Windows

Linux

64 bit version required

Data scheme

schema-free

Fixed schema

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

optional

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

yes

Embedded SQL for jBASE in BASIC

yes

but no triggers and foreign keys

APIs and other access methods

in-process shared library

JDBC
ODBC
RESTful HTTP API
WebSocket

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

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

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++
JavaScript (Node.js)
Python

.Net
Basic
Jabbascript
Java

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

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

Server-side scripts

Stored procedures

yes

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

yes

Triggers

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

Sharding

hash partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

yes, but depending on the SQL-Server Edition

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

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes, multi-version concurrency control (MVCC)

yes

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

User concepts

Access control

Database file passwords

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

Fine grained access control via users, groups and roles

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