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DBMS > BigObject vs. Ehcache vs. TigerGraph vs. Vertica

System Properties Comparison BigObject vs. Ehcache vs. TigerGraph vs. Vertica

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonEhcache  Xexclude from comparisonTigerGraph  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesA widely adopted Java cache with tiered storage optionsA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-timeCloud 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 modelRelational DBMS infoa hierachical model (tree) can be imposedKey-value storeGraph DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.19
Rank#329  Overall
#146  Relational DBMS
Score4.64
Rank#68  Overall
#8  Key-value stores
Score1.80
Rank#138  Overall
#13  Graph DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitebigobject.iowww.ehcache.orgwww.tigergraph.comwww.vertica.com
Technical documentationdocs.bigobject.iowww.ehcache.org/­documentationdocs.tigergraph.comvertica.com/­documentation
DeveloperBigObject, Inc.Terracotta Inc, owned by Software AGOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2015200920172005
Current release3.10.0, March 202212.0.3, January 2023
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen Source infoApache Version 2; commercial licenses availablecommercialcommercial 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 languageJavaC++C++
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
All OS with a Java VMLinuxLinux
Data schemeyesschema-freeyesYes, 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 dateyesyesyesyes
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.nononono
Secondary indexesyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like query language (GSQL)Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
JCacheGSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesJavaC++
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresLuanoyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes infoCache Event Listenersnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoby using Terracotta Serverhorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoby using Terracotta ServerMulti-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 methodsnonoyesno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneTunable Consistency (Strong, Eventual, Weak)Immediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesnoyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyes infosupports JTA and can work as an XA resourceACIDACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyes
Durability infoSupport for making data persistentyesyes infousing a tiered cache-storage approachyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
User concepts infoAccess controlnonoRole-based access controlfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
BigObjectEhcacheTigerGraphVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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BigObjectEhcacheTigerGraphVertica infoOpenText™ Vertica™
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