DBMS > Splice Machine
Splice Machine System Properties
Please select another system to compare it with Splice Machine.
|Editorial information provided by DB-Engines|
|Description||Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark|
|Primary database model||Relational DBMS|
|License Commercial or Open Source||Open Source AGPL 3.0, commercial license available|
|Cloud-based only Only available as a cloud service||no|
|DBaaS offerings (sponsored links) Database as a Service|
Providers of DBaaS offerings, please contact us to be listed.
|Server operating systems||Linux|
|Typing predefined data types such as float or date||yes|
|SQL Support of SQL||yes|
|APIs and other access methods||JDBC|
Native Spark Datasource
|Supported programming languages||C#|
|Server-side scripts Stored procedures||yes Java|
|Partitioning methods Methods for storing different data on different nodes||Shared Nothhing Auto-Sharding, Columnar Partitioning|
|Replication methods Methods for redundantly storing data on multiple nodes||Multi-source replication|
|MapReduce Offers an API for user-defined Map/Reduce methods||Yes, via Full 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, multi-version concurrency control (MVCC)|
|Durability Support for making data persistent||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||Access rights for users, groups and roles according to SQL-standard|
|More information provided by the system vendor|
THE ONLY SCALE-OUT SQL RDBMS WITH BUILT-IN MACHINE LEARNING
For data-rich, real-time applications with embedded AI/ML
Splice Machine brings together OLTP, OLAP, ML in one platform to deliver the capabilities applications need to be intelligent and scale.
-Scale-out architecture with auto-sharding handles any workload at any scale
-Create, deploy and manage your ML models at any scale.
-Deploy on public or private clouds or on-premises with Kubernetes.
|Typical application scenarios|
|Licensing and pricing models|
Kubernetes Community Edition: https://hub.helm.sh/charts/splicemachine/splice-helm
Free Trial: https://cloud.splicemachine.io/register
Data Lineage Doesn’t Have to be Hard
Feature Stores Need an HTAP Database
What Is a Feature Store?
Related products and services
We invite representatives of vendors of related products to contact us for presenting information about their offerings here.
|Recent citations in the news|
Splice Machine Announces Livewire, the Operational AI Platform Designed for Industrial Use Cases
provided by Google News
Hadoop Developer / Admin Jr
Share this page