DBMS > Hyprcubd vs. Ignite vs. Splice Machine
System Properties Comparison Hyprcubd vs. Ignite vs. Splice Machine
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|Editorial information provided by DB-Engines|
|Name||Hyprcubd Xexclude from comparison||Ignite Xexclude from comparison||Splice Machine Xexclude from comparison|
|Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.|
|Description||Serverless Time Series DBMS||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.||Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark|
|Primary database model||Time Series DBMS||Key-value store|
|Developer||Hyprcubd, Inc.||Apache Software Foundation||Splice Machine|
|Current release||Apache Ignite 2.6||3.1, March 2021|
|License Commercial or Open Source||commercial||Open Source Apache 2.0||Open Source AGPL 3.0, commercial license available|
|Cloud-based only Only available as a cloud service||yes||no||no|
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|Implementation language||Go||C++, Java, .Net||Java|
|Server operating systems||hosted||Linux|
|Typing predefined data types such as float or date||yes time, int, uint, float, string||yes||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.||no||yes|
|SQL Support of SQL||SQL-like query language||ANSI-99 for query and DML statements, subset of DDL||yes|
|APIs and other access methods||gRPC (https)||HDFS API|
RESTful HTTP API
Native Spark Datasource
|Supported programming languages||C#|
|Server-side scripts Stored procedures||no||yes (compute grid and cache interceptors can be used instead)||yes Java|
|Triggers||no||yes (cache interceptors and events)||yes|
|Partitioning methods Methods for storing different data on different nodes||Sharding||Shared Nothhing Auto-Sharding, Columnar Partitioning|
|Replication methods Methods for redundantly storing data on multiple nodes||yes (replicated cache)||Multi-source replication|
|MapReduce Offers an API for user-defined Map/Reduce methods||no||yes (compute grid and hadoop accelerator)||Yes, via Full Spark Integration|
|Consistency concepts Methods to ensure consistency in a distributed system||Eventual Consistency||Immediate Consistency||Immediate Consistency|
|Foreign keys Referential integrity||no||no||yes|
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data||no||ACID||ACID|
|Concurrency Support for concurrent manipulation of data||no||yes||yes, multi-version concurrency control (MVCC)|
|Durability Support for making data persistent||yes||yes||yes|
|In-memory capabilities Is there an option to define some or all structures to be held in-memory only.||no||yes||yes|
|User concepts Access control||token access||Security Hooks for custom implementations||Access rights for users, groups and roles according to SQL-standard|
|More information provided by the system vendor|
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