DBMS > Ignite vs. Microsoft SQL Server vs. TerminusDB vs. Vertica

System Properties Comparison Ignite vs. Microsoft SQL Server vs. TerminusDB vs. Vertica

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Editorial information provided by DB-Engines

Name

Description

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Microsofts flagship relational DBMS

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Graph DBMS

Relational DBMS

Column oriented

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
RDF store

Spatial DBMS
Time Series DBMS

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

Score	3.64
Rank	#89	Overall
	#13	Key-value stores
	#48	Relational DBMS

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Score	0.22
Rank	#323	Overall
	#28	Graph DBMS

Score	11.40
Rank	#43	Overall
	#27	Relational DBMS

Website

ignite.apache.org

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

terminusdb.com

www.vertica.com

Technical documentation

apacheignite.readme.io/docs

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

terminusdb.github.io/terminusdb/#

vertica.com/documentation

Developer

Apache Software Foundation

Microsoft

DataChemist Ltd.

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2015

1989

2018

2005

Current release

Apache Ignite 2.6

SQL Server 2022, November 2022

11.0.0, January 2023

12.0.3, January 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

GPL V3

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++, Java, .Net

C++

Prolog, Rust

C++

Server operating systems

Linux
OS X
Solaris
Windows

Linux
Windows

Linux

Data scheme

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

yes

SQL-like query language (WOQL)

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

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

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

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

JavaScript
Python

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

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

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

yes

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes (cache interceptors and events)

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Graph Partitioning

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes, but depending on the SQL-Server Edition

Journaling Streams

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

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

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

Role-based access control

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customers

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing models

Cost-based models and subscription-based models are both available. One license is...
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