DBMS > EsgynDB vs. RocksDB vs. SAP Adaptive Server

System Properties Comparison EsgynDB vs. RocksDB vs. SAP Adaptive Server

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Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	36.31
Rank	#25	Overall
	#17	Relational DBMS

Website

www.esgyn.cn

rocksdb.org

www.sap.com/products/technology-platform/sybase-ase.html

Technical documentation

github.com/facebook/rocksdb/wiki

help.sap.com/docs/SAP_ASE

Developer

Esgyn

Facebook, Inc.

SAP, Sybase

Initial release

2015

2013

1987

Current release

8.11.4, April 2024

16.0

License

Commercial or Open Source

commercial

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++, Java

C++

C and C++

Server operating systems

Linux

AIX
HP-UX
Linux
Solaris
Unix
Windows

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

APIs and other access methods

ADO.NET
JDBC
ODBC

C++ API
Java API

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

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C
C++
Go
Java
Perl
Python
Ruby

C
C++
Cobol
Java
Java
Perl
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

Java and Transact-SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

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

fine grained access rights according to SQL-standard

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