DBMS > Databend vs. Datomic vs. EJDB vs. Microsoft SQL Server vs. SingleStore

System Properties Comparison Databend vs. Datomic vs. EJDB vs. Microsoft SQL Server vs. SingleStore

Editorial information provided by DB-Engines

Name

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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

Primary database model

Relational DBMS

Document store

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	0.28
Rank	#287	Overall
	#131	Relational DBMS

Score	1.55
Rank	#144	Overall
	#67	Relational DBMS

Score	0.13
Rank	#331	Overall
	#46	Document stores

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	4.02
Rank	#74	Overall
	#39	Relational DBMS

Website

github.com/datafuselabs/databend
www.databend.com

www.datomic.com

github.com/Softmotions/ejdb

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

www.singlestore.com

Technical documentation

docs.databend.com

docs.datomic.com

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

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

docs.singlestore.com

Developer

Databend Labs

Cognitect

Softmotions

Microsoft

SingleStore Inc.

Initial release

2021

2012

1989

2013

Current release

1.0.59, April 2023

1.0.7180, July 2024

SQL Server 2022, November 2022

8.5, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

limited edition free

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

Rust

Java, Clojure

C++

C++, Go

Server operating systems

hosted
Linux
macOS

All OS with a Java VM

server-less

Linux
Windows

Linux

64 bit version required

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

SQL

Support of SQL

yes

but no triggers and foreign keys

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

RESTful HTTP API

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

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

Clojure
Java

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

Server-side scripts

Stored procedures

yes

Transaction Functions

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

yes

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

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

But extensive use of caching in the application peers

none

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

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

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

recommended only for testing and development

yes

User concepts

Access control

Users with fine-grained authorization concept, user roles

fine grained access rights according to SQL-standard

Fine grained access control via users, groups and roles

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