DB-EnginesExtremeDB: mitigate connectivity issues in a DBMSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Lovefield vs. Splice Machine vs. SwayDB vs. Teradata Aster

System Properties Comparison Lovefield vs. Splice Machine vs. SwayDB vs. Teradata Aster

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameLovefield  Xexclude from comparisonSplice Machine  Xexclude from comparisonSwayDB  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionEmbeddable relational database for web apps written in pure JavaScriptOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storagePlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSRelational DBMSKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.33
Rank#286  Overall
#131  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score0.04
Rank#387  Overall
#61  Key-value stores
Websitegoogle.github.io/­lovefieldsplicemachine.comswaydb.simer.au
Technical documentationgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdsplicemachine.com/­how-it-works
DeveloperGoogleSplice MachineSimer PlahaTeradata
Initial release2014201420182005
Current release2.1.12, February 20173.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license availableOpen Source infoGNU Affero GPL V3.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScriptJavaScala
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariLinux
OS X
Solaris
Windows
Linux
Data schemeyesyesschema-freeFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyesnoyes
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.nonoyes infoin Aster File Store
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like query language infovia JavaScript builder patternyesnoyes
APIs and other access methodsJDBC
Native Spark Datasource
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesJavaScriptC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Java
Kotlin
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnoyes infoJavanoR packages
TriggersUsing read-only observersyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneShared Nothhing Auto-Sharding, Columnar PartitioningnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
noneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoYes, via Full Spark Integrationnoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic execution of operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infousing MemoryDByesyesno
User concepts infoAccess controlnoAccess rights for users, groups and roles according to SQL-standardnofine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
LovefieldSplice MachineSwayDBTeradata Aster
Recent citations in the news

Kagiso interactive shares: all eyes on android at google I/O
11 May 2015, WhaTech

provided by Google News

Machine learning data pipeline outfit Splice Machine files for insolvency
26 August 2021, The Register

Splice Machine Launches the Splice Machine Feature Store to Simplify Feature Engineering and Democratize Machine ...
19 January 2021, PR Newswire

Distributed SQL System Review: Snowflake vs Splice Machine
18 September 2019, Towards Data Science

Splice Machine Launches Feature Store to Simplify Feature Engineering
19 January 2021, Datanami

ETL: The Silent Killer of Big Data Projects
23 July 2015, insideBIGDATA

provided by Google News

Teradata Enhances Big Data Analytics Platform
31 May 2024, Data Center Knowledge

Northwestern Analytics Partners with Teradata Aster to Host Hackathon
23 May 2014, Northwestern Engineering

Teradata Provides the Simplest Way to Bring the Science of Data to the Art of Business
22 September 2011, PR Newswire

Teradata's Aster shows how the flowers of fraud bloom
23 April 2015, The Register

Case study: Siemens reduces train failures with Teradata Aster
12 September 2016, RCR Wireless News

provided by Google News



Share this page

Featured Products

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Present your product here