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DBMS > Realm vs. TigerGraph vs. TimescaleDB vs. Vertica

System Properties Comparison Realm vs. TigerGraph vs. TimescaleDB vs. Vertica

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Editorial information provided by DB-Engines
NameRealm  Xexclude from comparisonTigerGraph  Xexclude from comparisonTimescaleDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-timeA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelDocument storeGraph DBMSTime Series DBMSRelational DBMS infoColumn oriented
Secondary database modelsRelational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.60
Rank#52  Overall
#9  Document stores
Score1.83
Rank#139  Overall
#13  Graph DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websiterealm.iowww.tigergraph.comwww.timescale.comwww.vertica.com
Technical documentationrealm.io/­docsdocs.tigergraph.comdocs.timescale.comvertica.com/­documentation
DeveloperRealm, acquired by MongoDB in May 2019TimescaleOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2014201720172005
Current release2.13.0, November 202312.0.3, January 2023
License infoCommercial or Open SourceOpen SourcecommercialOpen Source infoApache 2.0commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CC++
Server operating systemsAndroid
Backend: server-less
iOS
Windows
LinuxLinux
OS X
Windows
Linux
Data schemeyesyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes
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.nonoyesno
Secondary indexesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoSQL-like query language (GSQL)yes infofull PostgreSQL SQL syntaxFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsGSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languages.Net
Java infowith Android only
Objective-C
React Native
Swift
C++
Java
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresno inforuns within the applications so server-side scripts are unnecessaryyesuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes infoChange Listenersnoyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnoneyes, across time and space (hash partitioning) attributeshorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replication with hot standby and reads on replicas infoMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infoRelationships in graphsyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoIn-Memory realmnonono
User concepts infoAccess controlyesRole-based access controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
RealmTigerGraphTimescaleDBVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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More resources
RealmTigerGraphTimescaleDBVertica infoOpenText™ Vertica™
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