DBMS > Alibaba Cloud Table Store vs. GridGain vs. Stardog vs. Tkrzw

System Properties Comparison Alibaba Cloud Table Store vs. GridGain vs. Stardog vs. Tkrzw

Please select another system to include it in the comparison.

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

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

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Wide column store

Key-value store
Relational DBMS

Graph DBMS
RDF store

Key-value store

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

Score	0.31
Rank	#297	Overall
	#11	Wide column stores

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

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

www.alibabacloud.com/product/table-store

www.gridgain.com

www.stardog.com

dbmx.net/tkrzw

Technical documentation

www.alibabacloud.com/help/en/tablestore

www.gridgain.com/docs/index.html

docs.stardog.com

Developer

Alibaba

GridGain Systems, Inc.

Stardog-Union

Mikio Hirabayashi

Initial release

2016

2007

2010

2020

Current release

GridGain 8.5.1

7.3.0, May 2020

0.9.3, August 2020

License

Commercial or Open Source

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Open Source

Apache Version 2.0

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

Java

C++

Server operating systems

hosted

Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Linux
macOS

Data scheme

schema-free

yes

schema-free and OWL/RDFS-schema support

schema-free

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

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

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

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

HTTP API

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

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

Java
Python

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

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

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes (cache interceptors and events)

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes (replicated cache)

Multi-source replication in HA-Cluster

none

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

Immediate Consistency in HA-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

Atomic single-row operations

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

using specific database classes

User concepts

Access control

Access rights based on subaccounts and tokens

Security Hooks for custom implementations

Access rights for users and roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Top data analytics tools comparison: Alibaba Cloud, AWS, Azure, Google Cloud, IBM
5 December 2019, Wire19

Apache Software Foundation Announces New Top-Level Project Apache Paimon
16 April 2024, Datanami

Gartner’s Magic Quadrant for Cloud Database Management Systems
9 December 2020, CRN

25 Best Cloud Service Providers (Public and Private) in 2024
4 June 2023, CybersecurityNews

Apache Software Foundation Announces New Top-Level Project Apache Paimon
19 April 2024, Datanami

provided by Google News

GridGain in-memory data and generative AI – Blocks and Files
10 May 2024, Blocks & Files

GridGain's 2023 Growth Positions Company for Strong 2024
24 January 2024, PR Newswire

GridGain Unified Real-Time Data Platform Version 8.9 Addresses Today's More Complex Real-Time Data Processing ...
12 October 2023, GlobeNewswire

GridGain Showcases Power of Apache Ignite at Community Over Code Conference
5 October 2023, Datanami

GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2024
8 February 2024, PR Newswire

provided by Google News

Share this page