DBMS > DolphinDB vs. EJDB vs. Microsoft SQL Server vs. SingleStore vs. Sphinx

System Properties Comparison DolphinDB vs. EJDB vs. Microsoft SQL Server vs. SingleStore vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

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

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

Open source search engine for searching in data from different sources, e.g. relational databases

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	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	5.38
Rank	#62	Overall
	#35	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

www.dolphindb.com

github.com/Softmotions/ejdb

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

www.singlestore.com

sphinxsearch.com

Technical documentation

docs.dolphindb.cn/en/help200/index.html

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

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

docs.singlestore.com

sphinxsearch.com/docs

Developer

DolphinDB, Inc

Softmotions

Microsoft

SingleStore Inc.

Sphinx Technologies Inc.

Initial release

2018

2012

1989

2013

2001

Current release

v2.00.4, January 2022

SQL Server 2022, November 2022

8.5, January 2024

3.5.1, February 2023

License

Commercial or Open Source

commercial

free community version available

Open Source

GPLv2

commercial

restricted free version is available

commercial

free developer edition available

Open Source

GPL version 2, commercial licence available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C++, Go

C++

Server operating systems

Linux
Windows

server-less

Linux
Windows

Linux

64 bit version required

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

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

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

yes

but no triggers and foreign keys

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

in-process shared library

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

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

Proprietary protocol

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

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

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

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

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

horizontal partitioning

none

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

Sharding

hash partitioning

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes, but depending on the SQL-Server Edition

Source-replica replication

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

yes, multi-version concurrency control (MVCC)

yes

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.

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

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

yes

User concepts

Access control

Administrators, Users, Groups

fine grained access rights according to SQL-standard

Fine grained access control via users, groups and roles

More information provided by the system vendor

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Market metrics

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Licensing and pricing models

F ree Tier and Enterprise Edition
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