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DBMS > DolphinDB vs. Firebase Realtime Database vs. Hawkular Metrics vs. Hypertable vs. Splice Machine

System Properties Comparison DolphinDB vs. Firebase Realtime Database vs. Hawkular Metrics vs. Hypertable vs. Splice Machine

Editorial information provided by DB-Engines
NameDolphinDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHypertable  Xexclude from comparisonSplice Machine  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionDolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.An open source BigTable implementation based on distributed file systems such as HadoopOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelTime Series DBMSDocument storeTime Series DBMSWide column storeRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.13
Rank#80  Overall
#6  Time Series DBMS
Score14.29
Rank#39  Overall
#6  Document stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.dolphindb.comfirebase.google.com/­products/­realtime-databasewww.hawkular.orgsplicemachine.com
Technical documentationdocs.dolphindb.cn/­en/­help200/­index.htmlfirebase.google.com/­docs/­databasewww.hawkular.org/­hawkular-metrics/­docs/­user-guidesplicemachine.com/­how-it-works
DeveloperDolphinDB, IncGoogle infoacquired by Google 2014Community supported by Red HatHypertable Inc.Splice Machine
Initial release20182012201420092014
Current releasev2.00.4, January 20220.9.8.11, March 20163.1, March 2021
License infoCommercial or Open Sourcecommercial infofree community version availablecommercialOpen Source infoApache 2.0Open Source infoGNU version 3. Commercial license availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++Java
Server operating systemsLinux
Windows
hostedLinux
OS X
Windows
Linux
OS X
Windows infoan inofficial Windows port is available
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeschema-freeyes
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.nonono
Secondary indexesyesyesnorestricted infoonly exact value or prefix value scansyes
SQL infoSupport of SQLSQL-like query languagenononoyes
APIs and other access methodsJDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
Android
iOS
JavaScript API
RESTful HTTP API
HTTP RESTC++ API
Thrift
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
Java
JavaScript
Objective-C
Go
Java
Python
Ruby
C++
Java
Perl
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyeslimited functionality with using 'rules'nonoyes infoJava
TriggersnoCallbacks are triggered when data changesyes infovia Hawkular Alertingnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infobased on CassandraShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor infobased on Cassandraselectable replication factor on file system levelMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesyesnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, 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.yesnoyes
User concepts infoAccess controlAdministrators, Users, Groupsyes, based on authentication and database rulesnonoAccess rights for users, groups and roles according to SQL-standard

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More resources
DolphinDBFirebase Realtime DatabaseHawkular MetricsHypertableSplice Machine
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