DBMS > GridDB vs. Microsoft Access vs. RocksDB vs. SAP SQL Anywhere vs. TerminusDB

System Properties Comparison GridDB vs. Microsoft Access vs. RocksDB vs. SAP SQL Anywhere vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

Scalable in-memory time series database optimized for IoT and Big Data

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

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

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

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Secondary database models

Key-value store
Relational DBMS

Document store
RDF store

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

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

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

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

griddb.net

www.microsoft.com/en-us/microsoft-365/access

rocksdb.org

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

terminusdb.com

Technical documentation

docs.griddb.net

developer.microsoft.com/en-us/access

github.com/facebook/rocksdb/wiki

help.sap.com/docs/SAP_SQL_Anywhere

terminusdb.github.io/terminusdb/#

Developer

Toshiba Corporation

Microsoft

Facebook, Inc.

SAP

formerly Sybase

DataChemist Ltd.

Initial release

2013

1992

2013

1992

2018

Current release

5.1, August 2022

1902 (16.0.11328.20222), March 2019

8.11.4, April 2024

17, July 2015

11.0.0, January 2023

License

Commercial or Open Source

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

commercial

Bundled with Microsoft Office

Open Source

BSD

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++

Prolog, Rust

Server operating systems

Linux

Windows

Not a real database server, but making use of DLLs

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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

SQL92, SQL-like TQL (Toshiba Query Language)

yes

but not compliant to any SQL standard

yes

SQL-like query language (WOQL)

APIs and other access methods

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

ADO.NET
DAO
ODBC
OLE DB

C++ API
Java API

ADO.NET
HTTP API
JDBC
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

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

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

C
C++
Go
Java
Perl
Python
Ruby

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

JavaScript
Python

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

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

yes

Triggers

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

none

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

Source-replica replication

Database mirroring

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID at container level

ACID

but no files for transaction logging

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

in-memory journaling

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users can be defined per database

a simple user-level security was built in till version Access 2003

fine grained access rights according to SQL-standard

Role-based access control

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
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Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
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Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
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