DBMS > Alibaba Cloud Table Store vs. Apache Impala vs. GridDB vs. H2GIS vs. XTDB

System Properties Comparison Alibaba Cloud Table Store vs. Apache Impala vs. GridDB vs. H2GIS vs. XTDB

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

Analytic DBMS for Hadoop

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

Spatial extension of H2

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Secondary database models

Document store

Key-value store
Relational DBMS

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	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.alibabacloud.com/product/table-store

impala.apache.org

griddb.net

www.h2gis.org

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

impala.apache.org/impala-docs.html

docs.griddb.net

www.h2gis.org/docs/home

www.xtdb.com/docs

Developer

Alibaba

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Toshiba Corporation

CNRS

Juxt Ltd.

Initial release

2016

2013

2019

Current release

4.1.0, June 2022

5.1, August 2022

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

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

Open Source

LGPL 3.0

Open Source

MIT License

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++

Java

Clojure

Server operating systems

hosted

Linux

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

yes

yes, extensible-data-notation format

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL92, SQL-like TQL (Toshiba Query Language)

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

HTTP API

JDBC
ODBC

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

HTTP REST
JDBC

Supported programming languages

Java
Python

All languages supporting JDBC/ODBC

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

Java

Clojure
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

based on H2

Triggers

yes

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

selectable replication factor

Source-replica replication

yes

based on H2

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

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

Eventual Consistency

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

Atomic single-row operations

ACID at container level

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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 based on subaccounts and tokens

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Access rights for users can be defined per database

yes

based on H2

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.

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