DBMS > Fujitsu Enterprise Postgres vs. LevelDB vs. ObjectBox vs. Snowflake

System Properties Comparison Fujitsu Enterprise Postgres vs. LevelDB vs. ObjectBox vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

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

Extremely fast embedded database for small devices, IoT and Mobile

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Secondary database models

Document store
Spatial DBMS

Time Series DBMS

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

Score	0.37
Rank	#278	Overall
	#128	Relational DBMS

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

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

www.postgresql.fastware.com

github.com/google/leveldb

objectbox.io

www.snowflake.com

Technical documentation

www.postgresql.fastware.com/product-manuals

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

docs.objectbox.io

docs.snowflake.net/manuals/index.html

Developer

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Google

ObjectBox Limited

Snowflake Computing Inc.

Initial release

2011

2017

2014

Current release

Fujitsu Enterprise Postgres 14, January 2022

1.23, February 2021

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

Apache License 2.0

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 and C++

Server operating systems

Linux
Windows

Illumos
Linux
OS X
Windows

Android
iOS
Linux
macOS
Windows

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Proprietary native API

CLI Client
JDBC
ODBC

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

partitioning by range, list and by hash

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

online/offline synchronization between client and server

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

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

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.

User concepts

Access control

fine grained access rights according to SQL-standard

yes

Users with fine-grained authorization concept, user roles and pluggable authentication

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