DBMS > Apache Druid vs. etcd vs. Fauna vs. GridGain vs. Microsoft SQL Server

System Properties Comparison Apache Druid vs. etcd vs. Fauna vs. GridGain vs. Microsoft SQL Server

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

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

GridGain is an in-memory computing platform, built on Apache Ignite

Microsofts flagship relational DBMS

Primary database model

Relational DBMS
Time Series DBMS

Key-value store

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	1.52
Rank	#153	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

druid.apache.org

etcd.io
github.com/etcd-io/etcd

fauna.com

www.gridgain.com

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

Technical documentation

druid.apache.org/docs/latest/design

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

docs.fauna.com

www.gridgain.com/docs/index.html

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

Developer

Apache Software Foundation and contributors

Fauna, Inc.

GridGain Systems, Inc.

Microsoft

Initial release

2012

2014

2007

1989

Current release

29.0.1, April 2024

3.4, August 2019

GridGain 8.5.1

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache Version 2.0

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

Scala

Java, C++, .Net

C++

Server operating systems

Linux
OS X
Unix

FreeBSD
Linux
Windows

experimental

hosted

Linux
OS X
Solaris
Windows

Linux
Windows

Data scheme

yes

schema-less columns are supported

schema-free

yes

Typing

predefined data types such as float or date

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

SQL for querying

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

gRPC
JSON over HTTP

RESTful HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

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

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

C#
C++
Java
PHP
Python
Ruby
Scala

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

Server-side scripts

Stored procedures

user defined functions

yes (compute grid and cache interceptors can be used instead)

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

Triggers

yes, watching key changes

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

horizontal partitioning

consistent hashing

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

Multi-source replication

yes (replicated cache)

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate 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

Identity management, authentication, and access control

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

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