DBMS > AnzoGraph DB vs. Badger vs. OpenSearch vs. Sphinx vs. Splice Machine

System Properties Comparison AnzoGraph DB vs. Badger vs. OpenSearch vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

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

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Secondary database models

Vector DBMS

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

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	16.36
Rank	#37	Overall
	#4	Search engines

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Website

cambridgesemantics.com/anzograph

github.com/dgraph-io/badger

github.com/opensearch-project
opensearch.org

sphinxsearch.com

splicemachine.com

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

godoc.org/github.com/dgraph-io/badger

opensearch.org/docs/latest

sphinxsearch.com/docs

splicemachine.com/how-it-works

Developer

Cambridge Semantics

DGraph Labs

Amazon Web Services

Sphinx Technologies Inc.

Splice Machine

Initial release

2018

2017

2021

2001

2014

Current release

2.3, January 2021

2.5.0, January 2023

3.5.1, February 2023

3.1, March 2021

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

GPL version 2, commercial licence available

Open Source

AGPL 3.0, commercial license 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.

STACKIT OpenSearch offers OpenSearch in a managed version in enterprise grade, 100% GDPR-compliant, for a wide range of applications like analytics, website search, offering scalability and fast data access.
Aiven for OpenSearch: Fully managed open source search and analytics suite. Out-of-the-box integrations get you up and running in a couple of clicks.

Implementation language

Java

C++

Java

Server operating systems

Linux

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
OS X
Solaris
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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.

Secondary indexes

yes

All search fields are automatically indexed

yes

full-text index on all search fields

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

SQL-like query language

SQL-like query language (SphinxQL)

yes

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

Java API
RESTful HTTP/JSON API

Proprietary protocol

JDBC
Native Spark Datasource
ODBC

Supported programming languages

C++
Java
Python

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Java

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

Sharding

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

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

none

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

none

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

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

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

Access rights for users and roles

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

Specific characteristics

OpenSearch is a highly scalable and extensible open-source software suite for search,...
» more

Competitive advantages

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
» more

Typical application scenarios

The OpenSearch platform is used across a broad range of search , analytics, and observability...
» more

Licensing and pricing models

The OpenSearch Project offers open source software licensed under Apache License...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.