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DBMS > Databricks vs. Google Cloud Spanner vs. H2GIS vs. Tarantool

System Properties Comparison Databricks vs. Google Cloud Spanner vs. H2GIS vs. Tarantool

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonH2GIS  Xexclude from comparisonTarantool  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 horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Spatial extension of H2In-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelDocument store
Relational DBMS
Relational DBMSSpatial DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsRelational DBMSSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score0.08
Rank#368  Overall
#7  Spatial DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websitewww.databricks.comcloud.google.com/­spannerwww.h2gis.orgwww.tarantool.io
Technical documentationdocs.databricks.comcloud.google.com/­spanner/­docswww.h2gis.org/­docs/­homewww.tarantool.io/­en/­doc
DeveloperDatabricksGoogleCNRSVK
Initial release2013201720132008
Current release2.10.0, May 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoLGPL 3.0Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++
Server operating systemshostedhostedBSD
Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyesstring, double, decimal, uuid, integer, blob, boolean, datetime
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.yesnonono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyes infoQuery statements complying to ANSI 2011yesFull-featured ANSI SQL support
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Open binary protocol
Supported programming languagesPython
R
Scala
Go
Java
JavaScript (Node.js)
Python
JavaC
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyes infobased on H2Lua, C and SQL stored procedures
Triggersnoyesyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication with 3 replicas for regional instances.yes infobased on H2Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Foreign keys infoReferential integrityyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoStrict serializable isolationACIDACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes infobased on H2Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
More information provided by the system vendor
DatabricksGoogle Cloud SpannerH2GISTarantool
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksGoogle Cloud SpannerH2GISTarantool
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