DBMS > Hypertable vs. Ignite vs. Microsoft SQL Server vs. Teradata Aster vs. TerminusDB

System Properties Comparison Hypertable vs. Ignite vs. Microsoft SQL Server vs. Teradata Aster vs. TerminusDB

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

An open source BigTable implementation based on distributed file systems such as Hadoop

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

Platform for big data analytics on multistructured data sources and types

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

Primary database model

Wide column store

Key-value store
Relational DBMS

Relational DBMS

Graph DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
RDF store

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

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

ignite.apache.org

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

terminusdb.com

Technical documentation

apacheignite.readme.io/docs

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

terminusdb.github.io/terminusdb/#

Developer

Hypertable Inc.

Apache Software Foundation

Microsoft

Teradata

DataChemist Ltd.

Initial release

2009

2015

1989

2005

2018

Current release

0.9.8.11, March 2016

Apache Ignite 2.6

SQL Server 2022, November 2022

11.0.0, January 2023

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

Open Source

Apache 2.0

commercial

restricted free version is available

commercial

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

C++

C++, Java, .Net

C++

Prolog, Rust

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

Linux
OS X
Solaris
Windows

Linux
Windows

Linux

Data scheme

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

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

in Aster File Store

Secondary indexes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

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

yes

SQL-like query language (WOQL)

APIs and other access methods

C++ API
Thrift

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

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

ADO.NET
JDBC
ODBC
OLE DB

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

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

C
C#
C++
Java
Python
R

JavaScript
Python

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

R packages

yes

Triggers

yes (cache interceptors and events)

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

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

yes (replicated cache)

yes, but depending on the SQL-Server Edition

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

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

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