DBMS > Dgraph vs. Ehcache vs. Oracle vs. SAP SQL Anywhere vs. Sphinx

System Properties Comparison Dgraph vs. Ehcache vs. Oracle vs. SAP SQL Anywhere vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

A widely adopted Java cache with tiered storage options

Widely used RDBMS

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

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

dgraph.io

www.ehcache.org

www.oracle.com/database

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

sphinxsearch.com

Technical documentation

dgraph.io/docs

www.ehcache.org/documentation

docs.oracle.com/en/database

help.sap.com/docs/SAP_SQL_Anywhere

sphinxsearch.com/docs

Developer

Dgraph Labs, Inc.

Terracotta Inc, owned by Software AG

Oracle

SAP

formerly Sybase

Sphinx Technologies Inc.

Initial release

2016

2009

1980

1992

2001

Current release

3.10.0, March 2022

23c, September 2023

17, July 2015

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2; commercial licenses available

commercial

restricted free version is available

commercial

Open Source

GPL version 2, commercial licence available

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

C and C++

C++

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

AIX
HP-UX
Linux
OS X
Solaris
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

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

full-text index on all search fields

SQL

Support of SQL

yes

with proprietary extensions

yes

SQL-like query language (SphinxQL)

APIs and other access methods

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

JCache

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

ADO.NET
HTTP API
JDBC
ODBC

Proprietary protocol

Supported programming languages

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

Java

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

PL/SQL

also stored procedures in Java possible

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, horizontal partitioning

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

yes

by using Terracotta Server

Multi-source replication
Source-replica replication

Source-replica replication

Database mirroring

none

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable Consistency (Strong, Eventual, Weak)

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

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

Planned for future releases

fine grained access rights according to SQL-standard

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