DBMS > ArcadeDB vs. CockroachDB vs. SAP HANA vs. SQream DB

System Properties Comparison ArcadeDB vs. CockroachDB vs. SAP HANA vs. SQream DB

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Editorial information provided by DB-Engines

Name

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

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.

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

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.10
Rank	#358	Overall
	#48	Document stores
	#38	Graph DBMS
	#52	Key-value stores
	#35	Time Series DBMS

Score	5.73
Rank	#58	Overall
	#34	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Website

arcadedb.com

www.cockroachlabs.com

www.sap.com/products/hana.html

sqream.com

Technical documentation

docs.arcadedb.com

www.cockroachlabs.com/docs

help.sap.com/hana

docs.sqream.com

Developer

Arcade Data

Cockroach Labs

SAP

SQream Technologies

Initial release

2021

2015

2010

2017

Current release

September 2021

24.1.0, May 2024

2.0 SPS07 (April 4, 2023), April 2023

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0, commercial license 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

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Implementation language

Java

C++, CUDA, Haskell, Java, Scala

Server operating systems

All OS with a Java VM

Linux
macOS
Windows

Appliance or cloud-service

Linux

Data scheme

schema-free

dynamic schema

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language, no joins

yes, wire compatible with PostgreSQL

yes

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

JDBC

JDBC
ODBC

.Net
JDBC
ODBC

Supported programming languages

Java

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

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

SQLScript, R

user defined functions in Python

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

yes

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication using RAFT

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

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

Role-based access control

yes

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