DBMS > Cubrid vs. FeatureBase vs. LevelDB vs. Microsoft Azure Synapse Analytics

System Properties Comparison Cubrid vs. FeatureBase vs. LevelDB vs. Microsoft Azure Synapse Analytics

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Editorial information provided by DB-Engines

Name

Description

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Primary database model

Relational DBMS

Key-value store

Relational DBMS

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

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	0.31
Rank	#292	Overall
	#135	Relational DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Website

cubrid.com (korean)
cubrid.org (english)

www.featurebase.com

github.com/google/leveldb

azure.microsoft.com/services/synapse-analytics

Technical documentation

cubrid.org/manuals

docs.featurebase.com

github.com/google/leveldb/blob/main/doc/index.md

docs.microsoft.com/azure/synapse-analytics

Developer

CUBRID Corporation, CUBRID Foundation

Molecula and Pilosa Open Source Contributors

Google

Microsoft

Initial release

2008

2017

2011

2016

Current release

11.0, January 2021

2022, May 2022

1.23, February 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C, C++, Java

C++

Server operating systems

Linux
Windows

Linux
macOS

Illumos
Linux
OS X
Windows

hosted

Data scheme

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL queries

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

gRPC
JDBC
Kafka Connector
ODBC

ADO.NET
JDBC
ODBC

Supported programming languages

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

Java
Python

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C#
Java
PHP

Server-side scripts

Stored procedures

Java Stored Procedures

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

none

yes

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

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using Linux fsync

yes

with automatic compression on writes

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

yes

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