DBMS > Alibaba Cloud Table Store vs. GridDB vs. jBASE vs. MarkLogic vs. RocksDB

System Properties Comparison Alibaba Cloud Table Store vs. GridDB vs. jBASE vs. MarkLogic vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

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

A robust multi-value DBMS comprising development tools and middleware

Operational and transactional Enterprise NoSQL database

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

Primary database model

Wide column store

Time Series DBMS

Multivalue DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Key-value store

Secondary database models

Key-value store
Relational DBMS

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	5.92
Rank	#58	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#6	Search engines

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

Website

www.alibabacloud.com/product/table-store

griddb.net

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

www.marklogic.com

rocksdb.org

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.griddb.net

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

docs.marklogic.com

github.com/facebook/rocksdb/wiki

Developer

Alibaba

Toshiba Corporation

Rocket Software (formerly Zumasys)

MarkLogic Corp.

Facebook, Inc.

Initial release

2016

2013

1991

2001

2013

Current release

5.1, August 2022

5.7

11.0, December 2022

8.11.4, April 2024

License

Commercial or Open Source

commercial

Open Source

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

commercial

restricted free version is available

Open Source

BSD

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

C++

Server operating systems

hosted

Linux

AIX
Linux
Windows

Linux
OS X
Windows

Linux

Data scheme

schema-free

yes

schema-free

Schema can be enforced

schema-free

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

optional

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)

Embedded SQL for jBASE in BASIC

yes

SQL92

APIs and other access methods

HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

C++ API
Java API

Supported programming languages

Java
Python

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

.Net
Basic
Jabbascript
Java

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

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication

yes

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

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic single-row operations

ACID at container level

ACID

can act as a resource manager in an XA/JTA transaction

yes

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

yes, with Range Indexes

yes

User concepts

Access control

Access rights based on subaccounts and tokens

Access rights for users can be defined per database

Access rights can be defined down to the item level

Role-based access control at the document and subdocument levels

More information provided by the system vendor

Specific characteristics

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

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

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)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.