DBMS > AgensGraph vs. dBASE vs. GridGain vs. Snowflake vs. Teradata

System Properties Comparison AgensGraph vs. dBASE vs. GridGain vs. Snowflake vs. Teradata

Editorial information provided by DB-Engines

Name

Description

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

dBase was one of the first databases with a development environment on PC's. Its latest version dBase V is still sold as dBase classic, which needs a DOS Emulation. The up-to-date product is dBase plus.

GridGain is an in-memory computing platform, built on Apache Ignite

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

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series 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	9.70
Rank	#44	Overall
	#28	Relational DBMS

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Website

bitnine.net/agensgraph

Technical documentation

bitnine.net/documentation

www.dbase.com/support/knowledgebase

www.gridgain.com/docs/index.html

docs.snowflake.net/manuals/index.html

docs.teradata.com

Developer

Bitnine Global Inc.

Asthon Tate

GridGain Systems, Inc.

Snowflake Computing Inc.

Teradata

Initial release

2016

1979

2007

2014

1984

Current release

2.1, December 2018

dBASE 2019, 2019

GridGain 8.5.1

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

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

Java, C++, .Net

Server operating systems

Linux
OS X
Windows

DOS

dBase Classic
Windows

dBase Pro

Linux
OS X
Solaris
Windows

hosted

hosted
Linux

Data scheme

depending on used data model

yes

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

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

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes

ANSI-99 for query and DML statements, subset of DDL

yes

SQL 2016 + extensions

APIs and other access methods

Cypher Query Language
JDBC

none

The IDE can access other DBMS or ODBC-sources.

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

CLI Client
JDBC
ODBC

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

C
Java
JavaScript
Python

dBase proprietary IDE

C#
C++
Java
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

yes

The IDE can access stored procedures in other database systems.

yes (compute grid and cache interceptors can be used instead)

user defined functions

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes (cache interceptors and events)

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

none

Sharding

yes

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes (replicated cache)

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

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

not for dBase internal data, but IDE does support transactions when accessing external DBMS

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

Access rights for users and roles

Security Hooks for custom implementations

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

fine grained access rights according to SQL-standard

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