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DBMS > Apache Impala vs. EJDB vs. Google Cloud Spanner vs. RavenDB

System Properties Comparison Apache Impala vs. EJDB vs. Google Cloud Spanner vs. RavenDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonEJDB  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonRavenDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopEmbeddable document-store database library with JSON representation of queries (in MongoDB style)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.Open Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelRelational DBMSDocument storeRelational DBMSDocument store
Secondary database modelsDocument storeGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.31
Rank#296  Overall
#44  Document stores
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score2.84
Rank#101  Overall
#18  Document stores
Websiteimpala.apache.orggithub.com/­Softmotions/­ejdbcloud.google.com/­spannerravendb.net
Technical documentationimpala.apache.org/­impala-docs.htmlgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdcloud.google.com/­spanner/­docsravendb.net/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaSoftmotionsGoogleHibernating Rhinos
Initial release2013201220172010
Current release4.1.0, June 20225.4, July 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoGPLv2commercialOpen Source infoAGPL version 3, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CC#
Server operating systemsLinuxserver-lesshostedLinux
macOS
Raspberry Pi
Windows
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, bool, date, object_idyesno
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.nono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infoQuery statements complying to ANSI 2011SQL-like query language (RQL)
APIs and other access methodsJDBC
ODBC
in-process shared librarygRPC (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
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoyes
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneMulti-source replication with 3 replicas for regional instances.Multi-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes infousing Google Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate 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.
Foreign keys infoReferential integritynono infotypically not needed, however similar functionality with collection joins possibleyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoStrict serializable isolationACID, Cluster-wide transaction available
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyesyes
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.nono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Authorization levels configured per client per database

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More resources
Apache ImpalaEJDBGoogle Cloud SpannerRavenDB
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