DBMS > AgensGraph vs. EJDB vs. Google Cloud Bigtable vs. MySQL vs. SAP Advantage Database Server

System Properties Comparison AgensGraph vs. EJDB vs. Google Cloud Bigtable vs. MySQL 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

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Widely used open source RDBMS

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

Primary database model

Graph DBMS
Relational DBMS

Document store

Key-value store
Wide column store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Website

bitnine.net/agensgraph

github.com/Softmotions/ejdb

cloud.google.com/bigtable

www.mysql.com

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

Technical documentation

bitnine.net/documentation

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

cloud.google.com/bigtable/docs

dev.mysql.com/doc

Developer

Bitnine Global Inc.

Softmotions

Google

Oracle

since 2010, originally MySQL AB, then Sun

Sybase, SAP

Initial release

2016

2012

2015

1995

1993

Current release

2.1, December 2018

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

GPLv2

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

Server operating systems

Linux
OS X
Windows

server-less

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

Data scheme

depending on used data model

schema-free

yes

Typing

predefined data types such as float or date

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

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

Cypher Query Language
JDBC

in-process shared library

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

ADO.NET
JDBC
ODBC
Proprietary native API

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C
Java
JavaScript
Python

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

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Delphi
Perl
PHP

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

none

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Internal replication in Colossus, and regional replication between two clusters in different zones

Multi-source replication
Source-replica replication

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

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

yes

typically not needed, however similar functionality with collection joins possible

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

Atomic single-row operations

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

table locks or row locks depending on storage engine

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

caching of (temporary) tables can be configured

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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