DBMS > Bangdb vs. EJDB vs. SAP Advantage Database Server vs. SAP SQL Anywhere vs. Typesense

System Properties Comparison Bangdb vs. EJDB vs. SAP Advantage Database Server vs. SAP SQL Anywhere vs. Typesense

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

Converged and high performance database for device data, events, time series, document and graph

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

A typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity

Primary database model

Document store
Graph DBMS
Time Series DBMS

Document store

Relational DBMS

Search engine

Secondary database models

Spatial DBMS

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

Score	0.07
Rank	#346	Overall
	#47	Document stores
	#35	Graph DBMS
	#32	Time Series DBMS

Score	0.13
Rank	#331	Overall
	#46	Document stores

Score	3.50
Rank	#81	Overall
	#44	Relational DBMS

Score	0.80
Rank	#209	Overall
	#14	Search engines

Website

bangdb.com

github.com/Softmotions/ejdb

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

www.sap.com/products/technology-platform/sql-anywhere.html

typesense.org

Technical documentation

docs.bangdb.com

github.com/Softmotions/ejdb/blob/master/README.md

help.sap.com/docs/SAP_SQL_Anywhere

typesense.org/docs

Developer

Sachin Sinha, BangDB

Softmotions

Sybase, SAP

SAP

formerly Sybase

Initial release

2012

1993

1992

2015

Current release

BangDB 2.0, October 2021

17, July 2015

License

Commercial or Open Source

Open Source

BSD 3

Open Source

GPLv2

commercial

Open Source

GPL V3

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, C++

C++

Server operating systems

Linux

server-less

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

yes

schema-free

pre-defined schema optional

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

yes

string, integer, double, bool, date, object_id

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

in-process shared library

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

ADO.NET
HTTP API
JDBC
ODBC

RESTful HTTP API

Supported programming languages

C
C#
C++
Java
Python

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

Delphi
Perl
PHP

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

.Net

community maintained
Clojure

community maintained
Dart

community maintained
Go

community maintained
Java

community maintained
JavaScript
Perl

community maintained
PHP
Python
Ruby
Rust

community maintained
Swift

community maintained

Server-side scripts

Stored procedures

yes

yes, in C/C++, Java, .Net or Perl

Triggers

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

none

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

Source-replica replication

Database mirroring

Multi-source replication using RAFT

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes, run db with in-memory only mode

caching of (temporary) tables can be configured

yes

User concepts

Access control

yes (enterprise version only)

fine grained access rights according to SQL-standard

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