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DBMS > BigObject vs. Google Cloud Bigtable vs. Ignite vs. RavenDB vs. Teradata

System Properties Comparison BigObject vs. Google Cloud Bigtable vs. Ignite vs. RavenDB vs. Teradata

Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonIgnite  Xexclude from comparisonRavenDB  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Open Source Operational and Transactional Enterprise NoSQL Document DatabaseA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedKey-value store
Wide column store
Key-value store
Relational DBMS
Document storeRelational DBMS
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
Document store
Graph DBMS
Spatial 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
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score2.84
Rank#101  Overall
#18  Document stores
Score44.87
Rank#22  Overall
#15  Relational DBMS
Websitebigobject.iocloud.google.com/­bigtableignite.apache.orgravendb.netwww.teradata.com
Technical documentationdocs.bigobject.iocloud.google.com/­bigtable/­docsapacheignite.readme.io/­docsravendb.net/­docsdocs.teradata.com
DeveloperBigObject, Inc.GoogleApache Software FoundationHibernating RhinosTeradata
Initial release20152015201520101984
Current releaseApache Ignite 2.65.4, July 2022Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercialOpen Source infoApache 2.0Open Source infoAGPL version 3, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, Java, .NetC#
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
hostedLinux
OS X
Solaris
Windows
Linux
macOS
Raspberry Pi
Windows
hosted
Linux
Data schemeyesschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesnoyesnoyes
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.nonoyesyes
Secondary indexesyesnoyesyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLSQL-like DML and DDL statementsnoANSI-99 for query and DML statements, subset of DDLSQL-like query language (RQL)yes infoSQL 2016 + extensions
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresLuanoyes (compute grid and cache interceptors can be used instead)yesyes infoUDFs, stored procedures, table functions in parallel
Triggersnonoyes (cache interceptors and events)yesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShardingSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesnoneInternal replication in Colossus, and regional replication between two clusters in different zonesyes (replicated cache)Multi-source replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes (compute grid and hadoop accelerator)yesno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsACIDACID, Cluster-wide transaction availableACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsAuthorization levels configured per client per databasefine grained access rights according to SQL-standard

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More resources
BigObjectGoogle Cloud BigtableIgniteRavenDBTeradata
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