DBMS > Apache Doris vs. Hypertable vs. Microsoft SQL Server vs. OrigoDB vs. RavenDB

System Properties Comparison Apache Doris vs. Hypertable vs. Microsoft SQL Server vs. OrigoDB vs. RavenDB

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

An MPP-based analytics DBMS embracing the MySQL protocol

An open source BigTable implementation based on distributed file systems such as Hadoop

Microsofts flagship relational DBMS

A fully ACID in-memory object graph database

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Relational DBMS

Wide column store

Relational DBMS

Document store
Object oriented DBMS

Document store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.60
Rank	#247	Overall
	#113	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Website

doris.apache.org
github.com/apache/doris

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

origodb.com

ravendb.net

Technical documentation

github.com/apache/doris/wiki

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

origodb.com/docs

ravendb.net/docs

Developer

Apache Software Foundation, originally contributed from Baidu

Hypertable Inc.

Microsoft

Robert Friberg et al

Hibernating Rhinos

Initial release

2017

2009

1989

2009

under the name LiveDB

2010

Current release

1.2.2, February 2023

0.9.8.11, March 2016

SQL Server 2022, November 2022

5.4, July 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GNU version 3. Commercial license available

commercial

restricted free version is available

Open Source

AGPL version 3, commercial license available

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

Server operating systems

Linux

Linux
OS X
Windows

an inofficial Windows port is available

Linux
Windows

Linux
macOS
Raspberry Pi
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

SQL-like query language (RQL)

APIs and other access methods

JDBC
MySQL client

C++ API
Thrift

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

.NET Client API
HTTP API
LINQ

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

Java

C++
Java
Perl
PHP
Python
Ruby

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

.Net

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

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

yes

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

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

horizontal partitioning

client side managed; servers are not synchronized

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor on file system level

yes, but depending on the SQL-Server Edition

Source-replica replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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

fine grained access rights according to SQL-standard

Role based authorization

Authorization levels configured per client per database

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