DBMS > IBM Db2 Event Store vs. Microsoft SQL Server vs. NebulaGraph vs. Sphinx

System Properties Comparison IBM Db2 Event Store vs. Microsoft SQL Server vs. NebulaGraph vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

Microsofts flagship relational DBMS

A distributed, linear scalable, high perfomant Graph DBMS

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

Primary database model

Event Store
Time Series DBMS

Relational DBMS

Graph DBMS

Search engine

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	2.23
Rank	#116	Overall
	#10	Graph DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

www.ibm.com/products/db2-event-store

www.microsoft.com/en-us/sql-server

github.com/vesoft-inc/nebula
www.nebula-graph.io

sphinxsearch.com

Technical documentation

www.ibm.com/docs/en/db2-event-store

learn.microsoft.com/en-US/sql/sql-server

docs.nebula-graph.io

sphinxsearch.com/docs

Developer

IBM

Microsoft

Vesoft Inc.

Sphinx Technologies Inc.

Initial release

2017

1989

2019

2001

Current release

2.0

SQL Server 2022, November 2022

3.5.1, February 2023

License

Commercial or Open Source

commercial

free developer edition available

commercial

restricted free version is available

Open Source

Apache Version 2.0 + Common Clause 1.0

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

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Implementation language

C and C++

C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux
Windows

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

Strong typed schema

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

Nebula Graph internally uses the Key-Value store RocksDB for persistency. The vertices, edges, and their properties are stored as Key while their values are stored as Value. The primary indexes are per Key and secondary indexes are per Value.

yes

full-text index on all search fields

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

SQL-like query language

SQL-like query language (SphinxQL)

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Browser interface
console (shell)
Cypher Query Language
GO Object Graph Mapper
Java Object Graph Mapper
NGBatis

ORM framework for NebulaGraph and Spring-Boot
Proprietary native API
Python Object Graph Mapper
Query language nGQL

Proprietary protocol

Supported programming languages

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

.Net
C++
Go
Java
PHP
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

yes, but depending on the SQL-Server Edition

Causal Clustering using Raft protocol

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

No - written data is immutable

yes

Durability

Support for making data persistent

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

using RocksDB

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

User concepts

Access control

fine grained access rights according to SQL-standard

Role-based access control

More information provided by the system vendor

Specific characteristics

NebulaGraph is a truly distributed, linearly scalable, lightning-fast graph database,...
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Competitive advantages

NebulaGraph boasts the world's only graph database solution that is able to host...
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Typical application scenarios

Social networking Fraud detection Knowledge graph Data warehouse management Anti...
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Key customers

Companies from a variety of industries have implemented NebulaGraph Database in production,...
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Market metrics

At our very early stage, NebulaGraph has already received over 10,000 stars on GitHub...
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Licensing and pricing models

NebulaGraph is open source and free to use under Apache 2.0 license.
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