DBMS > EJDB vs. HEAVY.AI vs. Hypertable vs. Yanza

System Properties Comparison EJDB vs. HEAVY.AI vs. Hypertable vs. Yanza

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

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

An open source BigTable implementation based on distributed file systems such as Hadoop

Time Series DBMS for IoT Applications

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Website

github.com/Softmotions/ejdb

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

yanza.com

Technical documentation

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

docs.heavy.ai

Developer

Softmotions

HEAVY.AI, Inc.

Hypertable Inc.

Yanza

Initial release

2012

2016

2009

2015

Current release

5.10, January 2022

0.9.8.11, March 2016

License

Commercial or Open Source

Open Source

GPLv2

Open Source

Apache Version 2; enterprise edition available

Open Source

GNU version 3. Commercial license available

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++ and CUDA

C++

Server operating systems

server-less

Linux

Linux
OS X
Windows

an inofficial Windows port is available

Windows

Data scheme

schema-free

yes

schema-free

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

restricted

only exact value or prefix value scans

SQL

Support of SQL

yes

APIs and other access methods

in-process shared library

JDBC
ODBC
Thrift
Vega

C++ API
Thrift

HTTP API

Supported programming languages

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

All languages supporting JDBC/ODBC/Thrift
Python

C++
Java
Perl
PHP
Python
Ruby

any language that supports HTTP calls

Server-side scripts

Stored procedures

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

selectable replication factor on file system level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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