DBMS > Dgraph vs. EJDB vs. Heroic vs. Sphinx

System Properties Comparison Dgraph vs. EJDB vs. Heroic vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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

Primary database model

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

Score	1.39
Rank	#155	Overall
	#15	Graph DBMS

Score	0.13
Rank	#331	Overall
	#46	Document stores

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	5.97
Rank	#56	Overall
	#5	Search engines

Website

dgraph.io

github.com/Softmotions/ejdb

github.com/spotify/heroic

sphinxsearch.com

Technical documentation

dgraph.io/docs

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

spotify.github.io/heroic

sphinxsearch.com/docs

Developer

Dgraph Labs, Inc.

Softmotions

Spotify

Sphinx Technologies Inc.

Initial release

2016

2012

2014

2001

Current release

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPLv2

Open Source

Apache 2.0

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++

Server operating systems

Linux
OS X
Windows

server-less

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

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

via Elasticsearch

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language (SphinxQL)

APIs and other access methods

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

in-process shared library

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Proprietary protocol

Supported programming languages

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

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

yes

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

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

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.

User concepts

Access control

Planned for future releases

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More resources

DB-Engines blog posts

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

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