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DBMS > Apache IoTDB vs. Hawkular Metrics vs. Ingres vs. Microsoft Azure Synapse Analytics vs. Splice Machine

System Properties Comparison Apache IoTDB vs. Hawkular Metrics vs. Ingres vs. Microsoft Azure Synapse Analytics vs. Splice Machine

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonIngres  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSplice Machine  Xexclude from comparison
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 FlinkHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Well established RDBMSElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelTime Series DBMSTime Series DBMSRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteiotdb.apache.orgwww.hawkular.orgwww.actian.com/­databases/­ingresazure.microsoft.com/­services/­synapse-analyticssplicemachine.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.actian.com/­ingresdocs.microsoft.com/­azure/­synapse-analyticssplicemachine.com/­how-it-works
DeveloperApache Software FoundationCommunity supported by Red HatActian CorporationMicrosoftSplice Machine
Initial release201820141974 infooriginally developed at University Berkely in early 1970s20162014
Current release1.1.0, April 202311.2, May 20223.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercialcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaCC++Java
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Windows
AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
hostedLinux
OS X
Solaris
Windows
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nonono infobut tools for importing/exporting data from/to XML-files availableno
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLSQL-like query languagenoyesyesyes
APIs and other access methodsJDBC
Native API
HTTP REST.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
ADO.NET
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Go
Java
Python
Ruby
C#
Java
PHP
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyesnoyesTransact SQLyes infoJava
Triggersyesyes infovia Hawkular Alertingyesnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infobased on Cassandrahorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding, horizontal partitioningShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasselectable replication factor infobased on CassandraIngres ReplicatoryesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparknononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCCyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlyesnofine grained access rights according to SQL-standardyesAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache IoTDBHawkular MetricsIngresMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSplice Machine
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