DBMS > GraphDB vs. Heroic vs. Microsoft Azure Synapse Analytics vs. OpenSearch vs. SingleStore

System Properties Comparison GraphDB vs. Heroic vs. Microsoft Azure Synapse Analytics vs. OpenSearch vs. SingleStore

Editorial information provided by DB-Engines

Name

Description

Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.

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

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

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

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Primary database model

Secondary database models

Vector DBMS

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	3.25
Rank	#91	Overall
	#7	Graph DBMS
	#4	RDF stores

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	16.03
Rank	#37	Overall
	#4	Search engines

Score	5.38
Rank	#62	Overall
	#35	Relational DBMS

Website

www.ontotext.com

github.com/spotify/heroic

azure.microsoft.com/services/synapse-analytics

github.com/opensearch-project
opensearch.org

www.singlestore.com

Technical documentation

graphdb.ontotext.com/documentation

spotify.github.io/heroic

docs.microsoft.com/azure/synapse-analytics

opensearch.org/docs/latest

docs.singlestore.com

Social network pages

Developer

Ontotext

Spotify

Microsoft

Amazon Web Services

SingleStore Inc.

Initial release

2000

2014

2016

2021

2013

Current release

10.4, October 2023

2.5.0, January 2023

8.5, January 2024

License

Commercial or Open Source

commercial

Some plugins of GraphDB Workbench are open sourced

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2.0

commercial

free developer edition available

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.

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.
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.

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

Java

C++

Java

C++, Go

Server operating systems

All OS with a Java VM
Linux
OS X
Windows

hosted

All OS with a Java VM

Linux

64 bit version required

Data scheme

schema-free and OWL/RDFS-schema support; RDF shapes

schema-free

yes

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, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes

yes

via Elasticsearch

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC

yes

SQL-like query language

yes

but no triggers and foreign keys

APIs and other access methods

GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1

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

ADO.NET
JDBC
ODBC

Java API
RESTful HTTP/JSON API

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

Supported programming languages

.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C#
Java
PHP

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

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

Server-side scripts

Stored procedures

well-defined plugin interfaces; JavaScript server-side extensibility

Transact SQL

yes

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Sharding, horizontal partitioning

Sharding

hash partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Source-replica replication

stores two copies of each physical data partition on two separate nodes

MapReduce

Offers an API for user-defined Map/Reduce methods

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)

Eventual Consistency
Immediate Consistency

Immediate Consistency

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

yes

Constraint checking

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

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

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

In-memory capabilities

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

yes

User concepts

Access control

Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.

yes

Fine grained access control via users, groups and roles

More information provided by the system vendor

Specific characteristics

Ontotext GraphDB is a semantic database engine that allows organizations to build...
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OpenSearch is a highly scalable and extensible open-source software suite for search,...
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SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
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Competitive advantages

GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
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SingleStore’s competitive advantages include: Easy and Simplified Architecture with...
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Typical application scenarios

Metadata enrichment and management, linked data publishing, semantic inferencing...
» more

The OpenSearch platform is used across a broad range of search , analytics, and observability...
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Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more

Key customers

GraphDB provides a platform for building next-generation AI and Knowledge Graph...
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IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
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Market metrics

GraphDB is the most utilized semantic triplestore for mission-critical enterprise...
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Customers in various industries worldwide including US and International Industry...
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Licensing and pricing models

GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
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The OpenSearch Project offers open source software licensed under Apache License...
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F ree Tier and Enterprise Edition
» more

News

Riding the Databricks Wave with Hybrid Knowledge Graphs
6 June 2024

Matching Skills and Candidates with Graph RAG
31 May 2024

A Triple Store RAG Retriever
29 May 2024

Integrating GraphDB with Relational Database Systems
23 May 2024

Understanding the Graph Center of Excellence
17 May 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.