DBMS > Dgraph vs. Ehcache vs. Hive vs. SAP SQL Anywhere

System Properties Comparison Dgraph vs. Ehcache vs. Hive vs. SAP SQL Anywhere

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Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

A widely adopted Java cache with tiered storage options

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

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Graph DBMS

Key-value store

Relational DBMS

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

Score	1.54
Rank	#143	Overall
	#11	Graph DBMS

Score	6.47
Rank	#66	Overall
	#9	Key-value stores

Score	81.61
Rank	#17	Overall
	#11	Relational DBMS

Score	5.61
Rank	#72	Overall
	#40	Relational DBMS

Website

dgraph.io

www.ehcache.org

hive.apache.org

www.sap.com/products/sql-anywhere.html

Technical documentation

dgraph.io/docs

www.ehcache.org/documentation

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

help.sap.com/sql-anywhere

Developer

Dgraph Labs, Inc.

Terracotta Inc, owned by Software AG

Apache Software Foundation

initially developed by Facebook

SAP

formerly Sybase

Initial release

2016

2009

2012

1992

Current release

3.9.6, September 2021

3.1.2, August 2019

17, July 2015

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache Version 2

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

JCache

JDBC
ODBC
Thrift

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

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

Java

C++
Java
PHP
Python

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

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes, in C/C++, Java, .Net or Perl

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

by using Terracotta Server

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

yes

by using Terracotta Server

selectable replication factor

Source-replica replication

Database mirroring

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

Tunable Consistency (Strong, Eventual, Weak)

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

supports JTA and can work as an XA resource

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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

Planned for future releases

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

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