DBMS > BigObject vs. DolphinDB vs. Ehcache vs. PostGIS vs. SAP Advantage Database Server

System Properties Comparison BigObject vs. DolphinDB vs. Ehcache vs. PostGIS vs. SAP Advantage Database Server

Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Analytic DBMS for real-time computations and queries

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.

A widely adopted Java cache with tiered storage options

Spatial extension of PostgreSQL

Low-cost RDBMS with access to ISAM and FoxPro data structures

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Secondary database models

Relational DBMS

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	4.64
Rank	#68	Overall
	#8	Key-value stores

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Website

www.sap.com/products/advantage-database-server.html

Technical documentation

docs.bigobject.io

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

www.ehcache.org/documentation

postgis.net/documentation

Developer

BigObject, Inc.

DolphinDB, Inc

Terracotta Inc, owned by Software AG

Sybase, SAP

Initial release

2015

2018

2009

2005

1993

Current release

v2.00.4, January 2022

3.10.0, March 2022

3.4.2, February 2024

License

Commercial or Open Source

commercial

free community edition available

commercial

free community version available

Open Source

Apache Version 2; commercial licenses available

Open Source

GPL v2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
Windows

All OS with a Java VM

Linux
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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

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

JCache

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

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

Java

Delphi
Perl
PHP

Server-side scripts

Stored procedures

Lua

yes

user defined functions

yes

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

by using Terracotta Server

yes

based on PostgreSQL

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

by using Terracotta Server

yes

based on PostgreSQL

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

yes

supports JTA and can work as an XA resource

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

caching of (temporary) tables can be configured

User concepts

Access control

Administrators, Users, Groups

yes

based on PostgreSQL

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Recent citations in the news

Ehcache 2.0: Write-Behind Caching and JTA Support
11 May 2010, InfoQ.com

Atlassian asks customers to patch critical Jira vulnerability
22 July 2021, BleepingComputer

Hazelcast signs Java speed king to its in-memory data-grid crew
21 January 2014, The Register

Critical Jira Flaw in Atlassian Could Lead to RCE
22 July 2021, Threatpost

Scaling Australia's Most Popular Online News Sites with Ehcache
6 December 2010, InfoQ.com

provided by Google News

SAP Announces Q3 2023 Results: Asia Pacific and Japan View
19 October 2023, SAP News

provided by Google News

Share this page