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DBMS > Dgraph vs. Google Cloud Spanner vs. Ingres vs. Tarantool

System Properties Comparison Dgraph vs. Google Cloud Spanner vs. Ingres vs. Tarantool

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Editorial information provided by DB-Engines
NameDgraph  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonIngres  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionDistributed and scalable native Graph DBMSA 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.Well established RDBMSIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelGraph DBMSRelational DBMSRelational DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.53
Rank#152  Overall
#15  Graph DBMS
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websitedgraph.iocloud.google.com/­spannerwww.actian.com/­databases/­ingreswww.tarantool.io
Technical documentationdgraph.io/­docscloud.google.com/­spanner/­docsdocs.actian.com/­ingreswww.tarantool.io/­en/­doc
DeveloperDgraph Labs, Inc.GoogleActian CorporationVK
Initial release201620171974 infooriginally developed at University Berkely in early 1970s2008
Current release11.2, May 20222.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoCC and C++
Server operating systemsLinux
OS X
Windows
hostedAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
BSD
Linux
macOS
Data schemeschema-freeyesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyesyesstring, 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.nonono infobut tools for importing/exporting data from/to XML-files availableno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoyes infoQuery statements complying to ANSI 2011yesFull-featured ANSI SQL support
APIs and other access methodsGraphQL query language
gRPC (using protocol buffers) API
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
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Open binary protocol
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresnonoyesLua, C and SQL stored procedures
Triggersnonoyesyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesyesShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding, 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 nodesSynchronous replication via RaftMulti-source replication with 3 replicas for regional instances.Ingres ReplicatorAsynchronous 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 methodsnoyes 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 integritynoyes 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 infoMVCCyes, 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.nonoyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlno infoPlanned for future releasesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources
DgraphGoogle Cloud SpannerIngresTarantool
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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