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

System Properties Comparison Alibaba Cloud Table Store vs. Apache Impala vs. Bangdb 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

Converged and high performance database for device data, events, time series, document and graph

Spatial extension of H2

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

Primary database model

Wide column store

Relational DBMS

Document store
Graph DBMS
Time Series DBMS

Spatial DBMS

Document store

Secondary database models

Document store

Spatial 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	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	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

bangdb.com

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.bangdb.com

www.h2gis.org/docs/home

www.xtdb.com/docs

Developer

Alibaba

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Sachin Sinha, BangDB

CNRS

Juxt Ltd.

Initial release

2016

2013

2012

2013

2019

Current release

4.1.0, June 2022

BangDB 2.0, October 2021

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

BSD 3

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

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Implementation language

C++

C, 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

yes

schema-free

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL like support with command line tool

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

HTTP API

JDBC
ODBC

Proprietary protocol
RESTful HTTP API

HTTP REST
JDBC

Supported programming languages

Java
Python

All languages supporting JDBC/ODBC

C
C#
C++
Java
Python

Java

Clojure
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

based on H2

Triggers

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

selectable replication factor, Knob for CAP (enterprise version only)

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Tunable consistency, set CAP knob accordingly

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

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

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, run db with in-memory only mode

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

yes (enterprise version only)

yes

based on H2

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