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DBMS > Databricks vs. Infobright vs. Spark SQL vs. Vertica vs. YugabyteDB

System Properties Comparison Databricks vs. Infobright vs. Spark SQL vs. Vertica vs. YugabyteDB

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonInfobright  Xexclude from comparisonSpark SQL  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonYugabyteDB  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontendSpark SQL is a component on top of 'Spark Core' for structured data processingCloud 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.High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMSRelational DBMS infoColumn orientedRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.02
Rank#192  Overall
#90  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Score2.63
Rank#109  Overall
#53  Relational DBMS
Websitewww.databricks.comignitetech.com/­softwarelibrary/­infobrightdbspark.apache.org/­sqlwww.vertica.comwww.yugabyte.com
Technical documentationdocs.databricks.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlvertica.com/­documentationdocs.yugabyte.com
github.com/­yugabyte/­yugabyte-db
DeveloperDatabricksIgnite Technologies Inc.; formerly InfoBright Inc.Apache Software FoundationOpenText infopreviously Micro Focus and Hewlett PackardYugabyte Inc.
Initial release20132005201420052017
Current release3.5.0 ( 2.13), September 202312.0.3, January 20232.19, September 2023
License infoCommercial or Open Sourcecommercialcommercial infoThe open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016Open Source infoApache 2.0commercial infoLimited community edition freeOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.
Implementation languageCScalaC++C and C++
Server operating systemshostedLinux
Windows
Linux
OS X
Windows
LinuxLinux
OS X
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.depending on used data model
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.yesnononono
Secondary indexesyesno infoKnowledge Grid Technology used insteadnoNo Indexes Required. Different internal optimization strategy, but same functionality included.yes
SQL infoSupport of SQLwith Databricks SQLyesSQL-like DML and DDL statementsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.yes, PostgreSQL compatible
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
JDBC
ODBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL
Supported programming languagesPython
R
Scala
.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Java
Python
R
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesnonoyes, PostgreSQL PL/pgSQL, with minor differencesyes infosql, plpgsql, C
Triggersnonoyes, called Custom Alertsyes
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark Corehorizontal partitioning, hierarchical partitioningHash and Range Sharding, row-level geo-partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationnoneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyStrong consistency on writes and tunable consistency on reads
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACIDDistributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infobased on RocksDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnonono
User concepts infoAccess controlfine grained access rights according to SQL-standard infoexploiting MySQL or PostgreSQL frontend capabilitiesnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashyes
More information provided by the system vendor
DatabricksInfobrightSpark SQLVertica infoOpenText™ Vertica™YugabyteDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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YugabyteDB is an open source distributed SQL database for cloud native transactional...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Systems of record and engagement for cloud native applications that require resilience,...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Market metrics2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more
Apache 2.0 license for the database
» more

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More resources
DatabricksInfobrightSpark SQLVertica infoOpenText™ Vertica™YugabyteDB
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