DBMS > Apache Druid vs. Dolt vs. KeyDB vs. Microsoft SQL Server vs. Rockset

System Properties Comparison Apache Druid vs. Dolt vs. KeyDB vs. Microsoft SQL Server vs. Rockset

Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

A MySQL compatible DBMS with Git-like versioning of data and schema

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Microsofts flagship relational DBMS

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Relational DBMS
Time Series DBMS

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

Relational DBMS
Search engine

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	1.02
Rank	#191	Overall
	#89	Relational DBMS

Score	0.70
Rank	#229	Overall
	#32	Key-value stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Website

druid.apache.org

github.com/dolthub/dolt
www.dolthub.com

github.com/Snapchat/KeyDB
keydb.dev

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

rockset.com

Technical documentation

druid.apache.org/docs/latest/design

docs.dolthub.com

docs.keydb.dev

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

docs.rockset.com

Developer

Apache Software Foundation and contributors

DoltHub Inc

EQ Alpha Technology Ltd.

Microsoft

Rockset

Initial release

2012

2018

2019

1989

2019

Current release

29.0.1, April 2024

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache Version 2.0

Open Source

BSD-3

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C++

Server operating systems

Linux
OS X
Unix

Linux
macOS
Windows

Linux

Linux
Windows

hosted

Data scheme

yes

schema-less columns are supported

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

yes

dynamic typing

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

ingestion from XML files supported

Secondary indexes

yes

by using the Redis Search module

yes

all fields are automatically indexed

SQL

Support of SQL

SQL for querying

yes

Read-only SQL queries, including JOINs

APIs and other access methods

JDBC
RESTful HTTP/JSON API

CLI Client
HTTP REST

Proprietary protocol

RESP - REdis Serialization Protoco

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

HTTP REST

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

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

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

currently in alpha release

Lua

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Sharding

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

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

In-memory capabilities

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

yes

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Only one user is configurable, and must be specified in the config file at startup

simple password-based access control and ACL

fine grained access rights according to SQL-standard

Access rights for users and organizations can be defined via Rockset console

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