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DBMS > Databricks vs. InfinityDB vs. Ingres vs. ScyllaDB

System Properties Comparison Databricks vs. InfinityDB vs. Ingres vs. ScyllaDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonInfinityDB  Xexclude from comparisonIngres  Xexclude from comparisonScyllaDB  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.A Java embedded Key-Value Store which extends the Java Map interfaceWell established RDBMSCassandra and DynamoDB compatible wide column store
Primary database modelDocument store
Relational DBMS
Key-value storeRelational DBMSWide column store
Secondary database modelsKey-value 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
Score0.08
Rank#365  Overall
#55  Key-value stores
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score4.08
Rank#76  Overall
#5  Wide column stores
Websitewww.databricks.comboilerbay.comwww.actian.com/­databases/­ingreswww.scylladb.com
Technical documentationdocs.databricks.comboilerbay.com/­infinitydb/­manualdocs.actian.com/­ingresdocs.scylladb.com
DeveloperDatabricksBoiler Bay Inc.Actian CorporationScyllaDB
Initial release201320021974 infooriginally developed at University Berkely in early 1970s2015
Current release4.011.2, May 2022ScyllaDB Open Source 5.4.1, January 2024
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoOpen Source (AGPL), commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Scylla Cloud: Create real-time applications that run at global scale with Scylla Cloud, the industry’s most powerful NoSQL DBaaS
Implementation languageJavaCC++
Server operating systemshostedAll OS with a Java VMAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyesschema-free
Typing infopredefined data types such as float or dateyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyesyes
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.yesnono infobut tools for importing/exporting data from/to XML-files availableno
Secondary indexesyesno infomanual creation possible, using inversions based on multi-value capabilityyesyes infocluster global secondary indices
SQL infoSupport of SQLwith Databricks SQLnoyesSQL-like DML and DDL statements (CQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Proprietary protocol (CQL) infocompatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift
Supported programming languagesPython
R
Scala
JavaFor CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyesyes, Lua
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneIngres Replicatorselectable replication factor infoRepresentation of geographical distribution of servers is possible
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate ConsistencyEventual Consistency
Tunable Consistency infocan be individually decided for each write operation
Foreign keys infoReferential integrityno infomanual creation possible, using inversions based on multi-value capabilityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsACIDno infoAtomicity and isolation are supported for single operations
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCCyes
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.nononoyes infoin-memory tables
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess rights for users can be defined per object
More information provided by the system vendor
DatabricksInfinityDBIngresScyllaDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
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Competitive advantagesHighly-performant (efficiently utilizes full resources of a node and network; millions...
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Typical application scenariosScyllaDB is ideal for applications that require high throughput and low latency at...
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Key customersDiscord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
» more
Market metricsScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
» more
Licensing and pricing modelsScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
» more

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DatabricksInfinityDBIngresScyllaDB
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