DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Apache IoTDB vs. Heroic vs. SingleStore vs. SwayDB vs. Teradata Aster

System Properties Comparison Apache IoTDB vs. Heroic vs. SingleStore vs. SwayDB vs. Teradata Aster

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHeroic  Xexclude from comparisonSingleStore infoformer name was MemSQL  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.
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchMySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table typeAn 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 modelTime Series DBMSTime Series DBMSRelational DBMSKey-value storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score5.38
Rank#62  Overall
#35  Relational DBMS
Score0.04
Rank#387  Overall
#61  Key-value stores
Websiteiotdb.apache.orggithub.com/­spotify/­heroicwww.singlestore.comswaydb.simer.au
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlspotify.github.io/­heroicdocs.singlestore.com
DeveloperApache Software FoundationSpotifySingleStore Inc.Simer PlahaTeradata
Initial release20182014201320182005
Current release1.1.0, April 20238.5, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercial infofree developer edition availableOpen Source infoGNU Affero GPL V3.0commercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities
Implementation languageJavaJavaC++, GoScala
Server operating systemsAll OS with a Java VM (>= 1.8)Linux info64 bit version requiredLinux
Data schemeyesschema-freeyesschema-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 dateyesyesyesnoyes
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.nonononoyes infoin Aster File Store
Secondary indexesyesyes infovia Elasticsearchyesnoyes
SQL infoSupport of SQLSQL-like query languagenoyes infobut no triggers and foreign keysnoyes
APIs and other access methodsJDBC
Native API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Bash
C
C#
Java
JavaScript (Node.js)
Python
Java
Kotlin
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyesnoyesnoR packages
Triggersyesnononono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding infohash partitioningnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesSource-replica replication infostores two copies of each physical data partition on two separate nodesnoneyes 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 methodsIntegration with Hadoop and Sparknono infocan define user-defined aggregate functions for map-reduce-style calculationsnoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDAtomic execution of operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyesno
User concepts infoAccess controlyesFine grained access control via users, groups and rolesnofine grained access rights according to SQL-standard
More information provided by the system vendor
Apache IoTDBHeroicSingleStore infoformer name was MemSQLSwayDBTeradata Aster
Specific characteristicsSingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» more
Competitive advantagesSingleStore’s competitive advantages include: Easy and Simplified Architecture with...
» more
Typical application scenariosDriving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more
Key customersIEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more
Market metricsCustomers in various industries worldwide including US and International Industry...
» more
Licensing and pricing modelsF ree Tier and Enterprise Edition
» more

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
Apache IoTDBHeroicSingleStore infoformer name was MemSQLSwayDBTeradata Aster
DB-Engines blog posts

Turbocharge Your Application Development Using WebAssembly With SingleStoreDB
17 October 2022,  Akmal Chaudhri, SingleStore (sponsor) 

Cloud-Based Analytics With SingleStoreDB
9 June 2022,  Akmal Chaudhri, SingleStore (sponsor) 

SingleStore: The Increasing Momentum of Multi-Model Database Systems
14 February 2022,  Akmal Chaudhri, SingleStore (sponsor) 

show all

Recent citations in the news

AMD EPYC 4364P & 4564P @ DDR5-4800 / DDR5-5200 vs. Intel Xeon E-2488 Review
6 June 2024, Phoronix

TsFile: A Standard Format for IoT Time Series Data
27 February 2024, The New Stack

Linux 6.5 With AMD P-State EPP Default Brings Performance & Power Efficiency Benefits For Ryzen Servers
21 September 2023, Phoronix

Apache Promotes IoT Database Project
25 September 2020, Datanami

AMD EPYC 8324P / 8324PN Siena 32-Core Siena Linux Server Performance Review
10 October 2023, Phoronix

provided by Google News

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

provided by Google News

Building a Modern Database: Nikita Shamgunov on Postgres and Beyond
18 April 2024, Madrona Venture Group

SingleStore CEO sees little future for purpose-built vector databases
24 January 2024, VentureBeat

SingleStore Announces Real-time Data Platform to Further Accelerate AI, Analytics and Application Development
24 January 2024, businesswire.com

SingleStore adds indexed vector search to Pro Max release for faster AI work – Blocks and Files
29 January 2024, Blocks and Files

Announcing watsonx.ai and SingleStore for generative AI applications
15 November 2023, IBM

provided by Google News

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

Teradata unveils improved QueryGrid connectors
21 April 2015, CIO

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