DBMS > Apache Druid vs. GeoSpock vs. Microsoft SQL Server vs. Rockset vs. SurrealDB

System Properties Comparison Apache Druid vs. GeoSpock vs. Microsoft SQL Server vs. Rockset vs. SurrealDB

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

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

Spatial and temporal data processing engine for extreme data scale

Microsofts flagship relational DBMS

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

A fully ACID transactional, developer-friendly, multi-model DBMS

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Document store

Document store
Graph DBMS

Secondary database models

Time Series DBMS

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	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	1.02
Rank	#190	Overall
	#33	Document stores
	#18	Graph DBMS

Website

druid.apache.org

geospock.com

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

rockset.com

surrealdb.com

Technical documentation

druid.apache.org/docs/latest/design

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

docs.rockset.com

surrealdb.com/docs

Developer

Apache Software Foundation and contributors

GeoSpock

Microsoft

Rockset

SurrealDB Ltd

Initial release

2012

1989

2019

2022

Current release

29.0.1, April 2024

2.0, September 2019

SQL Server 2022, November 2022

v1.5.0, May 2024

License

Commercial or Open Source

Open Source

Apache license v2

commercial

restricted free version is available

commercial

Open Source

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

Java, Javascript

C++

Rust

Server operating systems

Linux
OS X
Unix

hosted

Linux
Windows

hosted

Linux
macOS
Windows

Data scheme

yes

schema-less columns are supported

yes

schema-free

Typing

predefined data types such as float or date

yes

dynamic typing

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

ingestion from XML files supported

Secondary indexes

yes

temporal, categorical

yes

all fields are automatically indexed

SQL

Support of SQL

SQL for querying

ANSI SQL for query only (using Presto)

yes

Read-only SQL queries, including JOINs

SQL-like query language

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC

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

HTTP REST

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

Go
Java
JavaScript (Node.js)
Python

Deno
Go
JavaScript (Node.js)
Rust

Server-side scripts

Stored procedures

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

Automatic 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

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Access rights for users can be defined per table

fine grained access rights according to SQL-standard

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

yes, based on authentication and database rules

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