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DBMS > Apache Ignite vs. ReductStore vs. Vertica

System Properties Comparison Apache Ignite vs. ReductStore vs. Vertica

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Editorial information provided by DB-Engines
NameApache Ignite  Xexclude from comparisonReductStore  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.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 modelKey-value store
Relational DBMS
Time Series DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.92
Rank#91  Overall
#15  Key-value stores
#48  Relational DBMS
Score0.01
Rank#379  Overall
#39  Time Series DBMS
Score9.38
Rank#42  Overall
#26  Relational DBMS
Websiteignite.apache.orggithub.com/­reductstore
www.reduct.store
www.vertica.com
Technical documentationapacheignite.readme.io/­docswww.reduct.store/­docsvertica.com/­documentation
DeveloperApache Software FoundationReductStore LLCOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201520232005
Current release2.16.0, December 20231.9, March 202412.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoBusiness Source License 1.1commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, Java, .NetC++, RustC++
Server operating systemsLinux
OS X
Solaris
Windows
Docker
Linux
macOS
Windows
Linux
Data schemeyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yesno
Secondary indexesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP APIADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
C++
JavaScript (Node.js)
Python
Rust
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)yes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes (cache interceptors and events)yes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)Multi-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)no infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlSecurity Hooks for custom implementationsfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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More resources
Apache IgniteReductStoreVertica infoOpenText™ Vertica™
Recent citations in the news

Real-time in-memory OLTP and Analytics with Apache Ignite on AWS | Amazon Web Services
14 May 2016, AWS Blog

What is Apache Ignite? How is Apache Ignite Used?
18 July 2022, The Stack

First Apache Ignite Summit Energizes Global Audience
10 June 2021, GlobeNewswire

Fire up big data processing with Apache Ignite
27 October 2016, InfoWorld

Apache Ignite 2.4 rolls out with Machine Learning and Spark DataFrames capabilities
19 March 2018, Packt Hub

provided by Google News

Introducing the Future of Data Analysis: A Revolutionary Tool for Vertica Users
25 October 2024, blogs.opentext.com

Vertica on Kubernetes
20 June 2024, blogs.opentext.com

Querying a Vertica data source in Amazon Athena using the Athena Federated Query SDK
11 February 2021, AWS Blog

What’s New in OpenText Vertica
10 January 2024, blogs.opentext.com

Postgres pioneer Michael Stonebraker promises to upend the database once more
26 December 2023, The Register

provided by Google News



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