DBMS > CockroachDB vs. DolphinDB vs. Microsoft SQL Server vs. Oracle vs. SAP HANA

System Properties Comparison CockroachDB vs. DolphinDB vs. Microsoft SQL Server vs. Oracle vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

Microsofts flagship relational DBMS

Widely used RDBMS

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	6.10
Rank	#58	Overall
	#33	Relational DBMS

Score	4.23
Rank	#82	Overall
	#6	Time Series DBMS

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Score	1234.27
Rank	#1	Overall
	#1	Relational DBMS

Score	45.84
Rank	#22	Overall
	#16	Relational DBMS

Website

www.cockroachlabs.com

www.dolphindb.com

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

www.oracle.com/database

www.sap.com/products/hana.html

Technical documentation

www.cockroachlabs.com/docs

docs.dolphindb.cn/en/help200/index.html

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

docs.oracle.com/en/database

help.sap.com/hana

Developer

Cockroach Labs

DolphinDB, Inc

Microsoft

Oracle

SAP

Initial release

2015

2018

1989

1980

2010

Current release

23.1.1, May 2023

v2.00.4, January 2022

SQL Server 2022, November 2022

23c, September 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

commercial

free community version available

commercial

restricted free version is available

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

C and C++

Server operating systems

Linux
macOS
Windows

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Appliance or cloud-service

Data scheme

dynamic schema

yes

Schemaless in JSON and XML columns

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

yes, wire compatible with PostgreSQL

SQL-like query language

yes

with proprietary extensions

yes

APIs and other access methods

JDBC

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

JDBC
ODBC

Supported programming languages

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

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

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Server-side scripts

Stored procedures

yes

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

PL/SQL

also stored procedures in Java possible

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

horizontal partitioning

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

Sharding, horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

yes

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can be realized in PL/SQL

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

yes

ACID

isolation level can be parameterized

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

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

Role-based access control

Administrators, Users, Groups

fine grained access rights according to SQL-standard

yes

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