DBMS > EJDB vs. Hive vs. Microsoft Azure Synapse Analytics vs. Oracle NoSQL vs. TimesTen

System Properties Comparison EJDB vs. Hive vs. Microsoft Azure Synapse Analytics vs. Oracle NoSQL vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

In-Memory RDBMS compatible to Oracle

Primary database model

Document store

Relational DBMS

Document store
Key-value store
Relational DBMS

Relational DBMS

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

github.com/Softmotions/ejdb

hive.apache.org

azure.microsoft.com/services/synapse-analytics

www.oracle.com/database/nosql/technologies/nosql

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

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

cwiki.apache.org/confluence/display/Hive/Home

docs.microsoft.com/azure/synapse-analytics

docs.oracle.com/en/database/other-databases/nosql-database/index.html

docs.oracle.com/database/timesten-18.1

Developer

Softmotions

Apache Software Foundation

initially developed by Facebook

Microsoft

Oracle

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2012

2016

2011

1998

Current release

3.1.3, April 2022

23.3, December 2023

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

GPLv2

Open Source

Apache Version 2

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

commercial

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++

Java

Server operating systems

server-less

All OS with a Java VM

hosted

Linux
Solaris SPARC/x86

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

optional

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

SQL-like DML and DDL statements

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

in-process shared library

JDBC
ODBC
Thrift

ADO.NET
JDBC
ODBC

RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

C++
Java
PHP
Python

C#
Java
PHP

C
C#
Go
Java
JavaScript (Node.js)
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Transact SQL

PL/SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Sharding, horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

yes

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

off heap cache

yes

User concepts

Access control

Access rights for users, groups and roles

yes

Access rights for users and roles

fine grained access rights according to SQL-standard

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