DBMS > Alibaba Cloud Table Store vs. EJDB vs. GeoMesa vs. HEAVY.AI

System Properties Comparison Alibaba Cloud Table Store vs. EJDB vs. GeoMesa vs. HEAVY.AI

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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

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Website

www.alibabacloud.com/product/table-store

github.com/Softmotions/ejdb

www.geomesa.org

github.com/heavyai/heavydb
www.heavy.ai

Technical documentation

www.alibabacloud.com/help/en/tablestore

github.com/Softmotions/ejdb/blob/master/README.md

www.geomesa.org/documentation/stable/user/index.html

docs.heavy.ai

Developer

Alibaba

Softmotions

CCRi and others

HEAVY.AI, Inc.

Initial release

2016

2012

2014

2016

Current release

4.0.5, February 2024

5.10, January 2022

License

Commercial or Open Source

commercial

Open Source

GPLv2

Open Source

Apache License 2.0

Open Source

Apache Version 2; enterprise edition available

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

Scala

C++ and CUDA

Server operating systems

hosted

server-less

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

HTTP API

in-process shared library

JDBC
ODBC
Thrift
Vega

Supported programming languages

Java
Python

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

All languages supporting JDBC/ODBC/Thrift
Python

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

depending on storage layer

Sharding

Round robin

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

depending on storage layer

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

Atomic single-row operations

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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.

depending on storage layer

yes

User concepts

Access control

Access rights based on subaccounts and tokens

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard

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More resources

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